Neurological prosthesis

ABSTRACT

A method improving or restoring neural function in a mammalian subject in need thereof, the method including: using an input receiver to record an input signal generated by a first set of nerve cells; using an encoder unit including a set of encoders to generate a set of coded outputs in response to the input signal; using the encoded outputs to drive an output generator; and using an output generator to activate a second set of nerve cells wherein the second set of nerve cells is separated from the first set of nerve cells by impaired set of signaling cells. In some embodiments, the second set of nerve cells produces a response that is substantially the same as the response in an unimpaired subject.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.13/230,488 (now U.S. Pat. No. 9,302,103; filed on Sep. 12, 2011), whichclaims the benefit under 35 U.S.C. § 119(e) of U.S. ProvisionalApplication No. 61/381,646 (filed on Sep. 10, 2010) and U.S. ProvisionalApplication No. 61/382,280 (filed Sep. 13, 2010). The subject matter ofthis application is also related to U.S. Provisional Application Nos.61/378,793 (filed on Aug. 31, 2010), 61/308,681 (filed on Feb. 26,2010), 61/359,188 (filed on Jun. 28, 2010), and 61/378,793 (filed onAug. 31, 2010), and International Patent Application Nos.PCT/US2011/26526 (filed Feb. 28, 2011) and PCT/US2011/026525 (filed Feb.28, 2011). The contents of each of the forgoing applications areincorporated by reference in their entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with U.S. Government support under R01 EY12978from National Institute of Health (NIH). The U.S. Government has certainrights in the invention.

FIELD

The present invention relates to methods and devices for restoring orimproving function, such as nerve function, in a subject. In particular,the present invention relates to methods and devices for restoring orimproving motor, auditory, or other function using a set of encodersthat closely mimic the input/output transformation of nerve cells toproduce near-normal, normal or even super-normal function in a subject.

BACKGROUND

A number of neurological disorders including, e.g., motor neurondisorders (e.g., damage from stroke, injury, diseases such as ALS andMS), psychiatric disorders, memory disorders, and auditory disordersinvolve the impairment of a set of nerve cells. In many cases, themalfunction of these cells prevents or degrades communication betweenhealthy sets of cells.

Various neural prosthetics have been developed to bypass malfunctioningcells to restore communication between the healthy cells. However, intypical cases, the bypassed impaired cells do not simply operate assignal pass-throughs, but instead provide processing of signals. Incases where a neural prosthetic does not accurately mimic the processingof the bypassed cells, the subject will exhibit degraded function incomparison to an unimpaired subject.

Thus, there exists a need to develop a neural prosthesis that bypassesor “jumps” impaired signaling cells, while providing a close proxy ofthe processing of the bypassed impaired signaling cells (i.e., such thatthe input to output transfer function of the prosthesis is well matchedto that which would have been exhibited by the bypassed signaling cellsin an unimpaired subject).

SUMMARY

As described in PCT/US2011/026525 (filed Feb. 28, 2011) (henceforth the“Retinal application”), the applicants have developed a method anddevice for restoring or improving vision, increasing visual acuity, ortreating blindness or visual impairment, or activating retinal cells.The method includes capturing a stimulus, encoding the stimulus,transforming the code into transducer instructions at an interface, andtransducing the instructions to retinal cells. The device includes a wayto capture a stimulus, a processing device executing a set of encoders,an interface, and a set of transducers, where each transducer targets asingle cell or a small number of cells; the set of transducers isreferred to as a high resolution transducer. In one embodiment, eachencoder executes a preprocessing step, a spatiotemporal transformingstep as well as an output-generating step. The method can be used for aretinal prosthesis to generate representations for a broad range ofstimuli, including artificial and natural stimuli.

The stimulus is converted or transformed into a proxy of normal retinaloutput, that is, a form of output the brain can readily interpret andmake use of as a representation of an image. The conversion occurs onabout the same time scale as that carried out by the normal ornear-normal retina, i.e., the initial retinal ganglion cell response toa stimulus occurs in a time interval ranging from about 5-300 ms. Themethods and devices described in the Retinal Application can helprestore near-normal to normal vision, or can improve vision, includingboth grayscale vision and color vision, in a patient or affected mammalwith any type of retinal degenerative disease where retinal ganglioncells (which may also be referred to herein as “ganglion cells”) remainintact.

The retina prosthesis, like the normal retina, is an image processor—itextracts essential information from the stimuli it receives, andreformats the information into patterns of action potentials the braincan understand. The patterns of action potentials produced by the normalretinal are in what is referred to as the retina's code or the ganglioncell's code. The retina prosthesis converts visual stimuli into thissame code, or a close proxy of it, so that the damaged or degeneratedretina can produce normal or near-normal output. Because the retinaprosthesis uses the same code as the normal retina or a close proxy ofit, the firing patterns of the ganglion cells in the damaged ordegenerated retina, that is, their patterns of action potentials are thesame, or substantially similar, to those produced by normal ganglioncells. A subject treated with such devices will have visual recognitionability closely matching the ability of a normal or near-normal subject.

The applicants have realized that this approach may be applied moregenerally to provide methods and devices for restoring or improvingfunction, such as neurological, motor, or auditory function in a humanpatient or other mammalian subject. As in the retinal case, a deviceincluding a processor which implements a set of encoders is providedwhich receives an input signal and generates an output signal, such thatthe input/output transformation operates as a close proxy of the signalprocessing that would occur in a normal patient.

In some embodiments, the input signal comes from a first set of healthycells (e.g., supplementary motor area neurons), and the output signaldrives a response in second set of healthy cells (e.g., spinal motorneurons) that are separated from the first set by an impaired set ofsignaling cells (e.g., damaged primary motor cortex neurons). Theencoders provide a close proxy of the processing that would occur in theset of signaling cells in an unimpaired subject, allowing the impairedcells to be bypassed or jumped while reducing or eliminating degradationin function.

In some embodiments, the input signal is an external stimulus (e.g.,sound waves), which are detected by the device (e.g., using amicrophone). The input signal is processed using a set of encoders togenerate a coded output used to drive healthy cells (e.g., spiralganglion cells in the inner ear) which are associated with an impairedset of signaling cells (e.g., cochlear hair cells used to detect soundin the inner ear). The encoders provide a close proxy of the processingthat would occur in the set of signaling cells in an unimpaired subject,allowing the impaired cells to be bypassed or jumped over, reducing oreliminating degradation in function.

To ensure that the encoders provide a close proxy of the processing thatwould occur in the signaling cells of a normal subject, a strategy maybe employed of using experimental data (e.g., collected in vivo or invitro from unimpaired cells) to generate a model of the signaling cells'processing. Accordingly, a data-driven phenomenological model isprovided, directly analogous to those developed to model retinalprocessing in the Retinal Application.

Because this approach leverages experimental data, the generatedencoders can accurately simulate the signaling cell processing, withoutrequiring a detailed abstract understanding of the signaling cells'underlying processing schemes. For example, it is believed that retinalprocessing in primates and humans highlights features in the visualstimulus useful for pattern recognition tasks (e.g., facial recognition)while de-emphasizing or eliminating other features (e.g., redundantinformation or noise) to allow for efficient processing in the brain.Similar processing occurs in many other types of cells or neuralnetworks (e.g., spinal motor neurons or motor neuron networks or spiralganglion cells in the ear, etc.). As of yet, there is no completeabstract understanding of the details of these natural processingschemes, which developed as the result natural selection over the courseof eons. However, despite this lack of abstract understanding, thedevices and techniques described herein can capture the benefit of thisprocessing, by accurately mimicking the response of unimpaired cells

A method improving or restoring neural function in a mammalian subjectin need thereof is disclosed, the method including: using an inputreceiver to record an input signal generated by a first set of nervecells; using an a encoder unit including a set of encoders to generate aset of coded outputs in response to the input signal; using the encodedoutputs to drive an output generator; and using an output generator toactivate a second set of nerve cells where the second set of nerve cellsis separated from the first set of nerve cells by impaired set ofsignaling cells; where the second set of nerve cells produces a responsethat is substantially the same as the response in an unimpaired subject.

In some embodiments, the first set of nerve cells includes supplementarymotor area neurons; the second set of nerve cells includes spinal motorneurons; and the impaired set of signaling cells includes primary motorcortex neurons.

Some embodiments include generating the input signal as a time resolvedseries of values {right arrow over (a)} corresponding to the pattern ofneural activity generated in the first set of nerve cells; andtransforming the values {right arrow over (a)} to a time resolved seriesof output values {right arrow over (c)} by applying a transformation.

In some embodiments, {right arrow over (c)} is a vector valued function,where each element of the vector is a value corresponding to a firingrate of a single cell or small group of cells from the second set ofnerve cells.

In some embodiments, {right arrow over (c)} is a vector valued function,where each element of the vector is a value corresponding to the totalfiring rate of second set of nerve cells.

In some embodiments, {right arrow over (c)} is a vector valued function,where each element of the vector is a value corresponding to the totalfiring rate of a respective subpopulation of the second set of nervecells.

In some embodiments, the second set of nerve cells includes motorneurons, and each subpopulation innervates a different respectivemuscle.

In some embodiments, the transformation includes: a set ofspatiotemporal linear filters; and a nonlinear function.

In some embodiments, the transformation is characterized by a set ofparameters; and where the set of parameters corresponds to a result offitting the transformation to experimental data obtained by: exposing anunimpaired subject to a broad range of reference stimuli; recording afirst response in the unimpaired subject corresponding to the first setof nerve cells; recording a second response in the unimpaired subjectcorresponding to the second set of nerve cells.

In some embodiments, the second response includes the firing rate ofindividual nerve cells.

In some embodiments, the spatiotemporal filters are parameterized by aset of K weights.

In some embodiments, the method of claim 11, where K is in the range of1-100 or any subrange thereof, e.g., in the range of 5-20.

In some embodiments, the nonlinear function is parameterized as a cubicspline function with M knots.

In some embodiments, M is in the range of 1-100 or any subrange thereof,e.g., in the range of 2-20.

In some embodiments, the spatiotemporal linear filters operate over Ptime bins, each having a duration Q.

In some embodiments, P is in the range of 1-100, or any subrangethereof, e.g., in the range of 5-20.

In some embodiments Q is in the range of 10 ms-100 ms. In someembodiments, Q is in the range of 1 ms-1000 ms or any subrange thereof.

In some embodiments, the broad range of reference stimuli includes atleast one chosen from the list consisting of: motion in an environmentincluding one or more obstacles; manipulation of objects havingdifferent weights; and moving a cursor to one of several locations on adisplay.

In some embodiments, the second set of nerve cells are light sensitized;and the step of using an output generator to activate a second set ofnerve cells includes: generating a time resolved optical signal; anddirecting the optical signal to the second set of nerve cells tostimulate a response.

Some embodiments include sensitizing the second set of nerve cells tolight

In some embodiments, the optical signal includes a spatially andtemporally modulated pattern of light.

In some embodiments, the modulated pattern of light includes an array ofpixels having an average pixel size of less than 0.1 mm and a pixelmodulation rate of greater than 100 Hz.

In some embodiments, the step of using an output generator to activate asecond set of nerve cells includes: generating a set of electricalpulses; and directing the electrical pulses the second set of nervecells to stimulate a response.

In another aspect, a device improving or restoring neural function in amammalian subject in need thereof is disclosed, the device including: aninput receiver configured to record an input signal generated by a firstset of nerve cells; an output generator configured to activate a secondset of nerve cells, where the second set of nerve cells is separatedfrom the first set of nerve cells by an impaired set of signaling cells;and an encoder unit including a set of encoders that generate a set ofcoded outputs in response to the input signal, where the set of codedoutputs control the output generator to activate the second set of nervecells to produce a response to the input signal that is substantiallythe same as the response in an unimpaired subject.

In some embodiments, the input receiver includes an electrode.

In some embodiments, the input receiver includes an array of electrodes.

In some embodiments, the array of electrodes records the response of atleast 100 neurons in the first set of neurons.

In some embodiments, the encoder unit includes at least one processor.

In some embodiments, the at least one processor includes a digitalsignal processor.

In some embodiments, the at least one processor includes multipleprocessors configured to operate in parallel.

In some embodiments, the output generator includes a set of electrodes.

In some embodiments, the output generator includes an optical signalgenerator.

In some embodiments, the optical signal generator includes a digitallight processor.

In some embodiments, the optical signal generator includes an array oflight emitting diodes.

In another aspect, a non-transitory computer readable media is disclosedhaving computer-executable instruction including instruction forexecuting steps including: recording an input signal generated by afirst set of nerve cells; using an a encoder unit including a set of setof encoders to generate a set of coded outputs in response to the inputsignal, and using the coded outputs to control an output generator toactivate a second set of nerve cells where the second set of nerve cellsis separated from the first set of neurons by an impaired set ofsignaling cells; where the second set of nerve cells produces a responseto the input signal that is substantially the same as the response in anunimpaired subject.

In another embodiments, a method of improving or restoring auditoryfunction in a mammalian subject in need thereof, is disclosed the methodincluding: using an audio receiver to generate an input signal inresponse to an audio stimulus; using an a encoder unit including a setof set of encoders to generate a set of coded outputs in response to theinput signal; using the encoded outputs to drive an output generator;and using an output generator to activate a set of auditory neurons,where the set of auditory neurons are associated with a set of impairedsignaling cells; where the auditory neurons produce a response that issubstantially the same as the response to the stimuli in an unimpairedsubject.

In some embodiments, the set of auditory neurons include spiral ganglioncells; and the impaired set of signaling cells includes cochlear haircells.

Some embodiments include generating the input signal as a time resolvedseries of values {right arrow over (a)} corresponding to the audiostimulus; transforming the values {right arrow over (a)} to a timeresolved series of output values {right arrow over (c)} by applying atransformation.

In some embodiments, {right arrow over (c)} is a vector valued function,where each element of the vector is a value corresponding the firingrate of a single spiral ganglion cell or small group of spiral ganglioncells from the set of auditory neurons.

In some embodiments, {right arrow over (c)} is a vector valued function,where each element of the vector is a value corresponding to the totalfiring rate of a respective subpopulation of the auditory set ofneurons.

In some embodiments, the transformation includes: a set ofspatiotemporal linear filters; and a nonlinear function.

In some embodiments, the transformation is characterized by a set ofparameters; and where the set of parameters corresponds to a result offitting the transformation to experimental data obtained by: exposing anunimpaired subject to a broad range of reference audio stimuli; andrecording a response in the unimpaired subject corresponding to the setof auditory neurons.

In some embodiments, the response includes the firing rate of individualneurons.

In some embodiments, the spatiotemporal filters are parameterized by aset of K weights.

In some embodiments, K is in the range of 1-100 or any subrange thereof,e.g., in the range of 5-20.

In some embodiments, the nonlinear function is parameterized as a cubicspline function with M knots.

In some embodiments, M is in the range of 1-100 or any subrange thereof,e.g., in the range of 2-20.

In some embodiments, the spatiotemporal linear filters operate over Ptime bins, each having a duration Q.

In some embodiments, P is in the range of 1-100 or any subrange thereof,e.g., in the range of 5-20.

In some embodiments, Q is in the range of 1 ms-1000 ms, or any subrangethereof, e.g., in the range of 10 ms-100 ms.

In some embodiments, the broad range of reference stimuli includesnatural sound and white noise stimuli.

In some embodiments, the set of auditory neurons are light sensitized;and the step of using an output generator to activate the set ofauditory neurons includes: generating a time resolved optical signal;and directing the optical signal to the second set of neurons tostimulate a response.

Some embodiments include sensitizing the second set of neurons to light.

In some embodiments, the optical signal includes a spatially andtemporally modulated pattern of light.

In some embodiments, the modulated pattern of light includes an array ofpixels having an average pixel size of less than 0.1 mm and a pixelmodulation rate of greater than 100 Hz.

In some embodiments, the step of using an output generator to activatethe set of auditory neurons includes: generating a set of electricalpulses; and directing the electrical pulses to the set of auditoryneurons to stimulate a response.

In another aspect, a device for improving or restoring auditory functionin a mammalian subject in need thereof is disclosed, the deviceincluding: an audio receiver configured to generate an input signal inresponse to an audio stimulus; an encoder unit including a set of set ofencoders configured to generate a set of coded outputs in response tothe input signal; and an output generator configured to, in response tothe set of coded outputs, activate a set of auditory neurons, where theset of auditory neurons are associated with a set of impaired signalingcells; where the second set of cells produces a response to a broadrange of stimuli that is substantially the same as the response to thestimuli in an unimpaired subject.

In some embodiments, the input receiver includes an audio transducerconfigured to convert an audio signal to a digital signal.

In some embodiments, the encoder unit includes at least one processor.

In some embodiments, the at least one processor includes a digitalsignal processor.

In some embodiments, the at least one processor includes multipleprocessors configured to operate in parallel.

In some embodiments, the output generator includes a set of electrodes.

In some embodiments, the output generator includes an optical signalgenerator.

In some embodiments, the optical signal generator includes a lightemitting diode array or a digital light processor.

In another aspect, a non-transitory computer readable media is disclosedhaving computer-executable instruction including instruction forexecuting steps including: generating an input signal in response to anaudio stimulus; controlling an encoder unit including a set of set ofencoders to generate a set of coded outputs in response to the inputsignal; and controlling an output generator to, in response to the setof coded outputs, activate a set of auditory neurons, where the set ofauditory neurons are associated with a set of impaired signaling cells;where the set of coded outputs control the output generator to activatethe set of auditory neurons to produce a response that is substantiallythe same as the response to the stimuli in an unimpaired subject.

Various embodiments may feature any of the elements, steps, devices,techniques, etc. described above, either alone or in any suitablecombination.

The terms prosthetic, prosthesis, prosthetic device, and prosthesisdevice are used interchangeably herein.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a schematic illustrating neural activity in a neural system,where signals from a set of cells labeled A are communicated through aset of cells labeled B to generate a response in a set of cells C.

FIG. 1B is a schematic illustrating the use of a neural prosthesis totreat impairment in the neural system of FIG. 1A.

FIG. 2 is a block diagram of a neural prosthesis.

FIG. 3 is a schematic diagram of a neural prosthesis.

FIG. 4 is a schematic diagram of a neural prosthesis featuring multipleencoders.

FIG. 5 is a functional block diagram of a processor for a neuralprosthesis.

FIG. 6A is a plot of a time dependent firing rate generated by anencoder of a neural prosthesis.

FIG. 6B is a plot of a digital pulse train generated based on the timedependent firing rate shown in FIG. 6A.

FIG. 6C is a plot of the pulsed output of a neural prosthesis traingenerated based on the digital pulse train of FIG. 6B.

FIG. 7 is a functional block diagram of a processor featuring a parallelprocessing architecture.

FIG. 8A is an illustration of a neural prosthesis deployed in and on ahuman subject.

FIG. 8B is an x-ray snapshot of an implanted portion of the neuralprosthesis of FIG. 8A.

FIG. 9 is functional block diagram of an auditory prosthesis.

FIG. 10A is a schematic of an auditory prosthesis featuring multipleoutput electrodes.

FIG. 10B is a schematic of an auditory prosthesis featuring multipleoutput light emitting diodes (LEDs).

FIG. 11A is a schematic illustration of a flexible LED array implantedin the cochlea of a subject.

FIG. 11B is a top down view of a flexible LED array of FIG. 12A prior toimplantation.

DETAILED DESCRIPTION

FIGS. 1A and 1B illustrate the operation of a neural prosthetic 100.FIG. 1A, illustrates the function of an unimpaired subject. A first setof neurons (A) sends signals to another set of neurons (B) and they, inturn, send signals to a third set (C). FIG. 1B illustrates the functionin an impaired subject, e.g., where the subject has suffered a strokethat damages set B. The neural prosthetic 100, bypasses or jumps (theterms are used interchangeably herein) the impaired nerves of set B.Using experimentally derived information about the transformationimplemented by the unimpaired set B in communicating signals from set Ato C, one can build the device 100 such that it mimics thetransformation. That is, the device 100 can produce a response in set C(e.g., a neural or nerve firing pattern) that closely mimics that whichwould normally occur when A sends out its signals to set C through anunimpaired set B. C can then send on normal signals to its downstreamneurons, and the patient can regain normal functioning. The encoderessentially jumps over B. (If the transformation is well modeled basedon experimental data, then this can be done for arbitrary signals fromA). To drive the neurons in C, several techniques are possible such asdriving optogenetic transducers (e.g., channelrhodopsin-2 or one of itsderivatives) or electrode based stimulation, as described in greaterdetail below.

In some embodiments, the signal from set A may be replaced by anexternal stimulus. This was the case in the Retinal Application, whereset B corresponded to damaged retinal cells (e.g., photoreceptors), setC corresponded to retinal ganglion cells, and the prosthesis 100received a visual stimulus (e.g., using a camera), processed thestimulus with encoders in a way that mimicked the processing of thedamaged retinal cells and circuitry (which would be analogous to B inFIG. 1B) and used a high resolution transducer to drive the retinalganglion cells to produce a response that closely matched that producedin an unimpaired subject. A similar approach may be used for restoringor improving auditory function, as detailed below.

As noted above, in some embodiments, a data-based phenomenologicalapproach is used in building the encoders for the prosthetic 100: Intypical cases, to build the encoder, one needs to finds thetransformation between the outside world (e.g., an external visual oraudio stimulus) and a set of neurons or between two sets of neurons.Below are three examples.

In the case of the prosthetic device for the retina, described in theRetinal Application, the encoder mimics the transformation betweenvisual stimuli (the outside world) and the retina's output cells—thatis, it jumps over the damaged sensory cells in the retina (thephotoreceptors) and interacts directly with the healthy cells (e.g.,ganglion cells), the retina's output cells, so that normal signals canbe sent to the brain.

In the case of an auditory prosthetic, the encoder mimics thetransformation between auditory stimuli (the outside world) and thecells in the auditory nerve—that is, it bypasses the damaged sensorycells (the hair cells of the inner ear) and interacts directly with theauditory nerve cells, the spiral ganglion cells, so normal soundinformation can be sent to the brain.

In the case of a motor prosthetic (the specific embodiment given below),the encoder mimics the transformation between Supplementary Motor Area(SMA) and spinal motor neurons (SMN)—that is, it jumps over the damagedprimary motor cortex (a area commonly damaged by strokes) and interactsdirectly with the healthy cells, the SMN (or the muscles they synapseon), so that normal muscle contractions/relaxations can be made.

This approach may be extended to a wide variety of other applications. Anon-limiting list of such applications is provided in Tables 2-6 foundtoward the end of this document.

To generate the data based model, the transformations performed by theencoders are worked out a priori (e.g., in an animal model or, usinghuman patients, i.e., using electrode implants and electromyography(EMG)). It's worked out by causing a large variety of patterns ofactivity to occur in the system and recording from the healthy neurons.

For example, to develop the encoder for the visual prosthetic,recordings were made from retina's output neurons, the ganglion cells,while the retina was presented with a wide variety of stimuli: thisallowed us to determine the transformation from visual stimuli toretinal ganglion cell firing spike patterns.

Likewise, in the case of the auditory prosthetic, recordings are made inthe spiral ganglion cells in the presence of a wide variety of auditorystimuli (e.g., including white noise and natural noise), so thetransformation between sound stimuli and the spiral ganglion cell spikepatterns can be determined.

In the case of the motor prosthetic, one may use two sets of recordings:one from neurons in the SMA and one from the spinal motor neurons thatcorrespond to them (e.g. to generate a set of encoders useful for armprosthetics, one may record from SMA neurons that affect arm movementsand from spinal motor neurons that control arm muscles), so one canobtain the transformation between the two sets of neurons (in this case,in FIG. 1B, set A would correspond to the SMA neurons that affect armmovements, and set C would correspond to the spinal motor neurons thatcontrol arm muscles).

In each of these example and other cases, visual, auditory, motor, orother, the approach is phenomenological: One parameterizes therelationship between the external stimuli and a set of neural signals orbetween two sets of neural signals, and one finds the parameter valuesusing an optimization procedure, such as maximum likelihood.

In many applications, an advantage of this approach is that it has thecapacity to generalize, that is, to mimic the processing of the impairedcells across a broad range of activity, because the approach uses amathematical transformation to capture the relation between the outsideworld and a set of neurons or between two sets of neurons, rather than,for example, a look up table. As indicated schematically in FIG. 1B, theprosthesis 100 is designed to take activity patterns of arbitrarycomplexity in set A and produce the outputs that normally occur in set Cas a result—that is, for most or all patterns that occur in A, themethod will be able to make C produce its normal output (e.g., nervefiring patterns). This is advantageous because normal brain activity iscomplex and variable and cannot be accurately characterized into a smallnumber of categories, as would be necessary for the more standard lookup table approach.

Note, in some examples presented herein the prosthesis device isdescribed as jumping or bypassing impaired cells. It is to be understoodthat in typical embodiments, the prosthetic does not simply reproducethe processing of specific impaired cells, but provides an accurateproxy of the input/output transformation that occurs in a normal subjectwhich converts a given input stimulus or neural activity at A into anoutput at C. That is, the prosthetic not only mimics the behavior of asubset of impaired cells in B, but instead acts as a proxy for theentire signally chain (potentially including both healthy and/orimpaired cells with various interactions) from A to C.

Motor Prosthesis

In one embodiment, the prosthesis 100 is employed to restore motorfunction in an impaired subject. Restoration of motor system function asis important for a number of reasons, including: a) damage to the motorsystem is the major source of disability in stroke and otherneurological disease (e.g., MS, primary lateral sclerosis (a form ofALS), cancers of the nervous system), b) major features of the motorsystem's anatomy map on to the A to B to C scheme described above inreference to FIGS. 1A and 1B, and c) the motor system is readilyaccessible to the required studies in animals and for implants inhumans. Thus, using the techniques described herein building a set ofencoders for applications is straightforward, and the return on theeffort is large—it can provide a remedy for a very broad range ofdisorders—that is, motor damage due to many different underlying causescan all be treated with the same set of encoders.

Normally, during voluntary movement, signals are transmitted from theSupplementary Motor Area (SMA) to Primary Motor Cortex (PMC) to SpinalMotor Neurons (SMN) to Muscle (M). The SMA corresponds to A in FIGS. 1Aand 1B, the PMC and its descending fibers correspond to B, and the SMN(and their axons) correspond to C. In some embodiments, the SMN can bejumped also (i.e., included as part of B), and stimulation can godirectly to muscle, which would then correspond to C.

In some cases, B is a particularly vulnerable part of the motor systembecause the pathway from PMC to the SMN is long—that is, the cell bodiesof the neurons lie in the cortex, but their axons descend through thethalamus, brain stem, and spinal cord. Thus strokes or other damage toany area along the pathway will interrupt their signals and cause motordeficits or outright paralysis.

Referring to FIG. 2, in some embodiments, the prosthesis 100 is a devicethat carries out the transformation of signals from A to C that isnormally carried out by interactions from A to B to C. The prosthesis100 includes an input receiver 101 (e.g., one or more electrodes) whichrecord an input signal generated by set of neurons in A (e.g., inresponse to a decision by the patient to make a movement, a motorcommand). A processor 102 (sometimes referred to herein as an encoderunit) processes the input signal using a set of encoders to generate aset of coded outputs. An output generator 103 (e.g. an electrode oroptical device of the types described herein), in response to the codedoutputs, activates the second set of neurons (neurons in C) to produce aresponse to the input signal, e.g., a response that is substantially thesame as the response in an unimpaired subject.

In some embodiments, an encoder implemented by the prosthesis 100operates using a model for the transformation, {right arrow over(c)}={right arrow over (f)}({right arrow over (a)}), where {right arrowover (a)} is the pattern of neural activity (expressed here as a nfiring rate as a function of time) in region A, and {right arrow over(c)} is the pattern of neural activity in region C. Both {right arrowover (a)} and {right arrow over (c)} are multivariate (they representthe activity of a population of neurons), so we represent them here asvector-valued functions of time. (Note that it's not critical tounderstand B at a mechanistic level, just to capture its input/outputrelation, as in the retinal prosthetic approach described in the RetinalApplication.)

Some embodiments employ a strategy adapted from those found to beeffective in the retina—that is, we choose the following parametricform, and we determine the parameters of the form by optimizing a costfunction separately for each output neuron (or small groups of outputneurons, e.g., containing less than 2, less than 3, less than 5, lessthan 10, less than 20, less than 30, less than 50, or less than 100neurons, e.g., in the range of 1-1000 neurons or any subrange thereof).

For example, for each output neuron, c_(i), we determine weightfunctions, {right arrow over (w)}_(i), and a nonlinearity, N_(i), sothat the modeled transformationc _(i) ^(fit) =N _(i)({right arrow over (a)}·{right arrow over(w)})  (1)is an optimal match to the actual transformation, c_(i)=f_(i)({rightarrow over (a)}), measured experimentally using the techniques describedherein. N_(i) is a pointwise nonlinearity, i.e., a function y=N_(i)(x),where x and y are both real-valued quantities (in the case of theretinal encoders, N_(i) was a cubic spline with 7 knots, but any othersuitable number may be used), and {right arrow over (w)} is a vector ofweights, specific to the output neuron i. {right arrow over (w)}_(i)consists of an array of quantities w_(i,j)(t), where i labels a neuronin the population C, j labels a neuron in the population A, and t istime. The ith component of the dot product {right arrow over (a)} iscalculated as follows:Σ_(j,t) a _(j)(t)w _(i,j)(t)As was the case for the encoders for the retina, the optimization isperformed to maximize the expected log likelihood over the entire outputpopulation, namely,

$L = \left\langle {\sum\limits_{i}\;{{ll}\left( {c_{i}^{fit},\overset{\rightarrow}{a}} \right)}} \right\rangle$ll(c_(i) ^(fit),{right arrow over (a)}) denotes the log likelihood thatc_(i) ^(fit) accounts for the observed activity of the ith neuron in C,when {right arrow over (a)} is the pattern of neural activity in regionA, and the brackets denote an average over all patterns of activityproduced in A. This likelihood is calculated from Poisson statisticsbased on the model firing rates (i.e., c_(i) ^(fit)).

The parametric form in eq. 1 builds on what we used for the retinaltransformation: the weights {right arrow over (w)}_(i), i.e., the arraysw_(i,j)(t) correspond to a set of spatiotemporal linear filters, becausethe subscripts i and j correspond to the positions of the neurons in Cand A, respectively, and N_(i) is an adjustable nonlinearity.

This overall strategy has several advantages—the linear-nonlinearcascade (LNC) can be used as a universal building block for anytransformation (Cybenko, 1989), it is a reasonable caricature of theinput/output transformation carried out by single neurons (or smallgroups of neurons), and there are optimization techniques that work wellwith complex, natural inputs, such as are present in area A. In theretina, the inputs were white noise and complex natural scenes. In themotor case, the inputs are the activity patterns that occur in A underfreely-moving behavior.

Constructing Encoders from Experimental Motor Activity Data

In some embodiments, the encoders implemented by the processor 102 areconstructed from data collected in two locations: the SMA and thetargeted muscles. Briefly, e.g., one may implant an array ofextracellular electrodes in SMA (e.g., as described in Hochberg et al,2006). This allows one to obtain firing patterns from one or more SMAneurons (e.g. in the range of 1-10,000 neurons, or any subrangethereof). At the same time, one may apply surface electrodes to thetargeted muscles to obtain electromyography signals (EMGs), as mentionedabove (see, e.g., Cescon et al, 2006), as this allows us to obtain thearray of activity patterns, c_(i).

Note, in various embodiments, one can use the EMG from each muscle todetermine the activity pattern in at least two ways: the EMG can beprocessed to count spikes (to obtain a total firing rate), or it can berectified and low pass filtered. In many applications, the firstapproach is the simplest and corresponds directly to the populationfiring rate, but there are practical advantages to using the second.Specifically, the rectified, low pass filtered signal will be dominatedby the larger motor units in the population, and since larger motor unitproduce more force by the muscle, this low pass filtered signalcorrelates more closely with the force command, and, therefore, isconsidered the more relevant quantity when aiming to control force.

Note that for a given c_(i), some SMA neurons may not be relevant forits control, and the model described herein accounts for this (theweights of these neurons will be zero or negligible). This is analogousto the situation with ganglion cells in the retina, where some regionsof an image (some pixels) are not relevant for a given ganglion cell'scontrol, and these pixels are given negligible weights.

To generate generalizable encoders, one adapt the strategy as was usedfor generating the retinal encoders: one may provoke the system with abroad range of stimuli. In the case of the retinal encoders, wepresented the retinas from normal subjects with two classes ofstimuli—artificial (white noise) and natural scenes—and recordedganglion cell responses. We then modeled the transformation fromstimulus to response. The “training” stimuli (the white noise andnatural scenes) were broad enough to produce a general model, one thatwas effective on any stimulus. In other words, given the trainingstimuli, we obtained a model that faithfully reproduced ganglion cellresponses to essentially any stimuli (stimuli of arbitrary complexity).

In the case of the motor system, one may adapt the same approach. Thenormal subject (e.g., a human, a non-human primate, a mouse, etc.)carries out a variety of artificial and natural movements, such aswalking on a wide variety of different and irregular terrains andgrades, and manipulating objects of different masses, and we recordresponses from SMA and from the muscles (e.g., using the surfaceelectrode EMG recordings). The irregular terrains and unpredictableloads are an example of a motor equivalent of white noise, and themovements on naturally changing terrain with predictable loads are anexample of a motor equivalent of natural scenes. In typicalapplications, the two together are the key elements for obtaininggeneralizable encoders. In various embodiments, other suitableactivities may be used.

Using the experimental the data sets generated in the previous step, onemay model the transformation between SMA recordings and EMG recordingsusing eq. 1. This gives a set of encoders, e.g., one for each muscle.

An alternative strategy to the one described above is to treat c_(i) asthe total firing rate of a subpopulation of neurons, rather than asingle neuron. This makes sense in the case of muscle activation becauseeach muscle is activated by a subpopulation of neurons, rather than asingle neuron, and the relevant variable for the subpopulation is totalfiring rate (at each moment in time). This firing rate can be obtainedfrom the branch of the peripheral nerve that innervates the muscle.Experimentally, the firing rate can be measured noninvasively usingsurface electrodes that are placed on the skin over the muscle; thesurface electrodes record an electromyography signal (EMG), from whichthe firing rate of the branch can be measured. (The EMG basically asurrogate for the total firing rate in the peripheral nerve branch thatinnervates the muscle.)

In this alternate strategy, each subpopulation c_(i) corresponds to thepopulation that innervates a different muscle. Thus, the transformationmodeled is the transformation from the activity is SMA to {right arrowover (c)}, the pattern of activity in the array of subpopulations.

Note that despite the apparent challenges of providing a transformationthat can cover the jump from supplementary motor area to spinal motorneurons (or muscle), experimental results obtained in the case ofretinal prosthetic techniques indicate that these challenges can bereadily overcome with the techniques described herein. In the case ofthe retinal prosthesis, the transformation jumped at least two synapsesand captured the output almost exactly (for both mouse and primatesubjects), as shown in the Retinal Application. Specifically, thetransformation was from image to ganglion cell output which requiredjumping all the operations from photoreceptors to bipolar cells toganglion cells, including the lateral actions of the horizontal cellsand the many types of amacrine cells. The jump in the motor system wouldbe, e.g., Supplementary Motor Layer 5→Motor Layer 4→Motor Layer2/3→Motor Layer 5→spinal motoneuron or muscle. A second related point isthat the approach might appear to be challenging due to the apparenthigh dimensionality in the motor context—that is, the motor cortex issignaling activity for movements related to many extremities—e.g., forthe legs, it's covering the hips, knees, ankles, feet, toes, etc. Butthe dimensionality is not as high as it seems because we treat the cellsas independent, a reasonable approximation as shown by Lee et al., 1998,Variability and Correlated Noise in the Discharge of Neurons in Motorand Parietal Areas of the Primate Cortex J. Neurosci, 18:1161; Averbackand Lee (2006) Effects of Noise Correlations on Information Encoding andDecoding, J Neurophysiol 95: 3633-3644, and because many (or all)transformations are carried out locally—that is, the transformationrequired for knee movements are laterally displaced in the tissue fromthose involved in ankle movements, etc, just as they are in the retina.(In the retina, transformations for different parts of visual space arecarried out locally, and the transformations can be carried out veryeffectively assuming conditional independence among the cells. Forexample, in some typical cases, each location in visual space is handledby about 10-30 cells—thus one doesn't have to perform an optimizationover thousands or even hundreds of neurons to obtain a goodrepresentation. Comparison of optimizations using large populations withthose using local populations pieced together as independent groupsindicates that local optimization provides satisfactory results.

It should be noted that the number of degrees of freedom for a movementis far, far less than in an image, and the motor system is much moreredundant. For example, in some typical situations: there are about2×10^6 optic nerve fibers (including both eyes), but roughly about 1/10that number of descending motor neurons (roughly 10^4 per spinalsegment, 30 spinal segments.) And on a per-cell basis, in typical cases,the motor system is also more redundant: there are about 1000, at least,motor neurons per muscle, even though only one time series (the forcegenerated by that muscle) must be specified. In some cases, for acomplete comparison one needs to compare contrast sensitivity andbandwidth for vision, with motor control precision and bandwidth, but intypical case these are comparable as well (1 part in 300 for visualcontrast sensitivity, motor control is, in many cases, not finer thanthat; e.g., corresponding to a ˜30-60 Hz bandwidth for both vision andmotor.)

The greater redundancy of the motor system is also indicated by clinicaland electromyographic results showing that about an 80% loss of motorneurons is typically required to have a clinical (functional) motordeficit.

Exemplary Implementation of Motor Prosthetic

Referring again to FIG. 2, the motor prosthetic 100, may incorporateencoders built using the techniques described here, e.g., implemented bythe processor 102. The encoders are used in conjunction with an inputreceiver 101 and an output generator 103.

As described herein, in various embodiments, the strategy is to firstdevelop encoders that capture the transformation from SMA activity tonerve branch activity (for arbitrary activity patterns), and, second, touse these encoders as an interface between SMA and the muscles (inpatients in which the connections have been severed or otherwiseimpaired (anywhere along the pathway from SMA to muscle).

In some embodiments, what the encoders do is jump over the damaged area(bridge the gap) in real time or near real time; the muscle receives thesignals or a close proxy of the signals it would normally receive—but itreceives them through the device instead of the normal biologicalcircuitry. Because the encoders mimic the normal transformations fromSMA all the way down to the branches of the nerves that directly commandthe muscle, they can restore normal or near-normal movements.

Referring to FIG. 3, in some embodiments the input receiver 101 includesa plurality of electrodes 301 embedded in the SMA (although threeelectrodes are shown, any suitable number may be used).

For example, in some embodiments, electrodes may be implanted in humanSMA using techniques of the type described in Hochberg et al, 2006:Action potentials (e.g., of individual neurons or small groups ofneurons) may be recorded, e.g., using a 10×10 array of siliconmicroelectrodes (e.g., of the type known in the art as a Utah array). Inone embodiment, electrodes 1 mm in length protrude from a 4 mm×4 mmplatform. Signals from the electrodes then pass through a titaniumpercutaneous connector to reach the outside environment. The connectoris then connected to a recording system, which carries out amplificationand unit identification on the signals from the electrodes, e.g., usingthe techniques described in Chestek et al, 2009. Note that in someembodiments, one may use single unit (e.g., single cell) activity as therelevant quantity in determining SMA activity. Additional oralternatively local field potential or multi-unit activity as recordedby each electrode in the array could play this role.

The measured SMA activity signals are then fed into the processor 102that performs the operations of the encoders. In some embodiments, theelectrodes and a battery pack are positioned subcutaneously, as in deepbrain stimulation (DBS) methods familiar in the art, e.g., as used forParkinson's patients. For this, a battery pack to drive the recordingsystem is put in subcutaneously in the anterior chest wall with leadstunneled up to a site in the scalp to supply power to the recordingsystem. An example of such a system is described in greater detailbelow.

The output of the encoders is then sent to muscle via the outputgenerator 103. As shown, the generator includes an array of outputelectrodes 302. Again, although three output electrodes are shown, anynumber may be used. In various embodiments, and suitable technique forstimulating the muscle may be used. In some embodiments, the generatormay be implemented using the techniques described in Moritz et al, 2008and/or Guiraud et al, 2006.

For example, in some embodiments, each encoder output, c_(i), determinesthe amplitude of the current pulse during a given time bin. In someembodiments, the time bins are typically 20 ms, following standardpractice for stimulating muscles at 50 Hz, however, any suitable timebin duration may be used. In some embodiments, the maximum current (peakof the current pulse) will follow standard practice (i.e., about 10 mA),however, any suitable value may be used.

In some embodiments, after device implantation, the encoder must beoptimized for the specific patient. For example, in the case of encodersused in prosthetics for humans, but based on experimental data fromnon-human primate subjects (e.g., monkeys) the optimization makes thenecessary correction, e.g., it takes into account the fact that theencoder was determined for monkey, and the SMA of a monkey and a humanare not the same size. Tuning may be accomplished in software in theencoder. In some embodiments, one may add a set of additional parametersto each encoder. These parameters determine the overall location andsize of the patch of input neurons corresponding to a_(j), as used ineq. 1. These parameters may be determined as follows for each targetmuscle: the patient is asked to attempt to execute a movement thatnormally results in contraction, isolated as well as possible to thatmuscle (note that because the patient cannot move the muscle because ofneurologic damage, no movement will occur, but SMA will be activatedbecause of the intent to move). The intent activates the neurons in theportion of the SMA that will provide the correct inputs to the encoderfor that muscle. The tuning parameters are systematically varied untilthe muscle is in fact activated. Note that this tuning process can beexpedited by functional Mill prior to implantation; this will narrowdown the relevant region of SMA for each muscle.

In some embodiments, after device implantation, a gain factor thatconverts the encoder's output to the amplitude of the current pulse maybe adjusted. This will be determined by asking the patient to makeisolated movements as in the previous step, and adjusting the gain toproduce the patient's desired output.

Exemplary Motor Prosthesis Device

FIG. 4 is a schematic diagram of an exemplary embodiments of the motorprosthesis 100. As shown the input receiver includes nine input devices401 (e.g., electrodes) for measuring the activity of single neurons orgroups of neurons in the SMA. The input signal measured by each inputdevice 401 is sent to a corresponding encoder in the processor 102 (eachencoder is represented as a vertical column).

The output of each processor is used to control a corresponding outputgenerator element (e.g., an electrode, digital micromirror deviceelement, or LED, as detailed below) 403 of the output generator 103. Theoutput of the output generator elements drive a response incorresponding muscle or SMN cells.

Execution of the encoders proceeds in a series of steps, indicated inthe figure as modules 402 a-c: preprocessing 402 a, spatiotemporaltransformation 402 b, and spike generation 402 c. The output of thespike generation step may be nontransiently stored in a storage module402 d in preparation for conversion to a format suitable output, whichmay include a burst elimination step (not shown). The output isgenerated by the output generator 103. Note that output may be in theform of current pulses delivered as in as in either Moritz et al, 2008or Guiraud et al, 2006 as is standard practice for stimulating muscles.Arrows show the flow of signals from specific regions of the SMA throughthe modules of the encoders, through output generator 103, which drivesmuscles or SMN.

Input Receiver

As noted above, in some embodiments, electrodes may be implanted inhuman SMA using techniques of the type described in Hochberg et al,2006: Action potentials (e.g., of individual neurons or small groups ofneurons) may be recorded, e.g., using a 10×10 array of siliconmicroelectrodes (e.g., of the type know in the art as a Utah array). Inone embodiment, electrodes 1 mm in length protrude from a 4 mm×4 mmplatform. Signals from the electrodes then pass through a titaniumpercutaneous connector to reach the outside environment. The connectoris then connected to a recording system, which carries out amplificationand unit identification on the signals from the electrodes, e.g., usingthe techniques described in Chestek et al, 2009. Note that in someembodiments, one may use single unit (e.g., single cell) activity as therelevant quantity in determining SMA activity. Additional oralternatively local field potential or multi-unit activity as recordedby each electrode in the array could play this role.

In other embodiments, any other suitable technique for measuring SMAactivity may be used.

Processor/Encoder

As noted above, in the case of a motor prosthetic (the specificembodiment given below), the encoder mimics the transformation betweenSupplementary Motor Area (SMA) and spinal motor neurons (SMN)—that is,it jumps over the damaged primary motor cortex (a area commonly damagedby strokes) and interacts directly with the healthy cells, the SMN (orthe muscles they synapse on), so that normal musclecontractions/relaxations can be made. These encoders use an algorithmthat converts input signal from the SMA into patterns of electricalsignals that are the same, or substantially similar, to that would beoutput in a normal subject. That is, the encoders jump all cells andcircuitry between the input cells (corresponding to A in FIG. 1B) andthe output cells (corresponding to C in FIG. 1B).

The prosthetic can use multiple encoders which can be assembled in aparallel manner as shown, for example, in FIG. 4, where differentsegments of the SMA activity are run through separate encoders, which,in turn, control different, specified output generator elements 403. Inthis embodiment, each encoder may have parameters suited for itsoperation, which may, for example, take into account the location and/ortype of signaling cells being emulated by the encoder or being driven bythe encoder's output. The term “code” can refer to a pattern ofelectrical pulses that corresponds to a pattern of action potentials(also referred to as spike trains) that the output cells produces inresponse to a stimulus or signals from upstream neurons. The term “code”may refer to bit streams corresponding to a pattern of spike trains.Each bit may correspond to the activity of one neuron (e.g., 1 means theneuron fires; 0 means the neuron does not fire). In other embodimentsthe bits correspond to other information (e.g., the firing rate of apopulation of neurons). The code may also be a continuous wave. Any typeof waveform may be encompassed by the present invention, includingnonperiodic waveforms and periodic waveforms, including but not limitedto, sinusoidal waveforms, square waveforms, triangle waveforms, orsawtooth waveforms.

FIG. 5 shows a functional block diagram illustrating an exemplaryembodiment of an encoder in the processor 102. As shown, the processor102 includes a number of processing modules corresponding to theencoder, each operatively connected with one, several, or all othermodules. The modules may be implemented on one or more processingdevices (e.g., as described in detail below). As used herein, a moduleis considered to be substantially implemented on a given processor ifsubstantially all essential computations associated with the function ofthe module are carried out on the processor.

The processor 102 includes a preprocessing module 501 which receives aninput signal from the input receiver 101 and, e.g., rescales the signalfor processing. In some embodiments, the preprocessing module implementsprocessing analogous to that described in the Retinal Applicationsubsection entitled “Preprocessing Step.”

A spatiotemporal transformation module 502 receives the output of thepreprocessing module and applies a spatiotemporal transformation (e.g.,analogous to that described in the subsection of the Retinal Applicationentitled “Spatiotemporal Transformation Step”) to generate, e.g., a setof firing rates corresponding to those that would have been generated bythe output cells, e.g., to a digital pulse generator. In someembodiments, the spatiotemporal transformation module 502 includes aspatial transformation module 502 a that convolves the input signal witha spatial kernel and a temporal transformation module 502 b thatconvolves the output of the spatial transformation module 502 b with atemporal kernel to generate a temporal transformation output. In otherembodiments, e.g., where the processing involves an encoder with anon-separable spatiotemporal transformation, separate spatial andtemporal transformation modules are not used.

In some embodiments, the processor 102 includes a nonlineartransformation module which 503 applies a nonlinear function to thespatiotemporal transformation output to generate the set of firing rates(e.g., as described in reference to Eq. 1 above). In some embodimentsthe nonlinear function is implemented using a look-up table.

A digital pulse generator module 505 generates digital pulse trainscorresponding to the firing rates output from one or more of the othermodules and generates a digital pulse train (i.e., a series of digitalpulses) corresponding to each firing rate. These pulse trains are thenoutput to the output generator 103. In some embodiments, the digitalpulse generator module 505 implements processing of the type describedin the subsection of the Retinal Application entitled “Spike GenerationStep.”

FIGS. 6A-6C show an example of the generation of a spike train outputbased on a calculated firing rate. FIG. 6A shows the time dependentfiring rate calculated by the encoder. FIG. 6B shows the correspondingspike train generated by the pulse generator module 505. FIG. 6C showsthe corresponding output of the output generator 103.

Referring back to FIG. 5, in some embodiments, an interpolation module506 is used to generate data having temporal resolution higher than themeasurement rate of the input receiver 101. In one embodiment, theinterpolation module 506 receives output from the spatiotemporaltransformation module 502, applies interpolation, and passes the resultson to the nonlinear transformation module 503. In other embodiments, theinterpolation may be applied after the nonlinear transformation, e.g.,to directly interpolate firing rates prior to input into the digitalpulse generator 506. In some embodiments, the interpolated informationhas a temporal resolution corresponding to at least 2, at least 5, atleast 10, at least 20, or at least 50 times or more the measurement rateof input receiver 101.

In some embodiments, a burst elimination module 507 is provided whichoperates on the output of the digital pulse generator module 505 toreduce or eliminate the presence of bursts. In some embodiments, theburst elimination module 507 implements burst elimination processinganalogous to the type described in the subsection of the RetinalApplication entitled “Spike Generation Step.”

FIG. 7 shows an exemplary embodiment of the processor 102 featuring adual processor architecture. As shown, the processor 102 includes ageneral purpose processor (GPP) and a digital signal processor (DSP),e.g., integrated onto a single chip. The GPP and DSP are connected to ashared memory (MEM). The processor 102 receives data from input receiver101, e.g., via the shared memory. The processor 102 outputs data, e.g.,to the output generator 103.

In one embodiment, the DSP is a Texas Instrument TMS320C64 seriesprocessor. The GPP is an ARM Cortex A8 processor, and the shared memoryis an SDRAM (e.g., with 512 MB of memory). In various embodiments, othersuitable processors known in the art may be used. Some embodiments mayfeature more than two parallel processors and more than one sharedmemory.

The platform shown in FIG. 7 is capable of highly-parallel computation.The processing flow may be pipelined, as described above, with theimplementation of various processing steps or modules divided betweenthe processors. In general, the more computationally expensiveprocessing tasks (e.g., tasks involving complicated matrix operations,convolutions, interpolation etc.) may be assigned to the DSP, with lessexpensive tasks (e.g., scaling operations, pulse generation, processsynchronization and other “housekeeping” tasks, etc.) may be assigned tothe GPP.

The table below shows an exemplary assignment of the processing steps.However, in other embodiments, different assignments may be made.

TABLE 1 Dual Processor Assignments Processing Step Processor AssignedPreprocessing GPP or DSP Spatial Transformation DSP TemporalTransformation DSP Interpolation DSP Nonlinearity GPP Digital PulseGeneration GPP Burst Elimination GPP Output GPP

In some embodiments, one, several, or all of the preprocessing module,the spatiotemporal transformation module, and the interpolation moduleare all substantially or entirely implemented of the DSP. In someembodiments, one, several, or all of the scaling module, nonlineartransformation module, the digital pulse generation module, and theburst elimination module may be substantially or entirely implemented ofthe GPP. This implementation of the modules may lead to a particularlyadvantageous processing throughput and reduced processing time. However,in various embodiments, other suitable implementations may be used.

Although some exemplary embodiments of a processor for the prostheticdevice 100 are set out above, it is to be understood that in variousembodiments, other processing devices may be used. The processingdevice, e.g., hand-held computer, can be implemented using any devicecapable of receiving a data and transforming them into output withacceptable speed and accuracy for the application at hand. Thisincludes, but is not limited to, a combination general purpose processor(GPP)/digital signal processor (DSP); a standard personal computer, or aportable computer such as a laptop; a graphical processing unit (GPU); afield-programmable gate array (FPGA) (or a field-programmable analogarray (FPAA), if the input signals are analog); an application-specificintegrated circuit (ASIC) (if an update is needed, the ASIC chip wouldneed to be replaced); an application-specific standard product (ASSP); astand-alone DSP; a stand-alone GPP; and the combinations thereof.

In one embodiment, the processing device is a hand-held computer(Gumstix Overo, Gumstix, San Jose, Calif.), based around a dual-coreprocessor (OMAP 3530, Texas Instruments, Dallas, Tex.) that integrates ageneral purpose processor (GPP) and a digital signal processor (DSP)onto a single chip. This platform is capable of highly-parallelcomputation and requires much less power than a typical portablecomputer (˜2 Watts or less, compared to 26 Watts for a standard laptopcomputer). This allows the transformation to be computed in real-time,on a device that is portable and can be powered on a single battery forlong periods of time. For example, typical laptop batteries, with chargecapacities in the range of 40-60 Watt-hours, could run the processorcontinuously for about 20-30 hours. In another embodiment, all or aportion the processing device is small in size so that it can be worn bya patient (as detailed below). In other embodiments, other suitablecomputing devices may be used, e.g., a Beagleboard device available fromTexas Instruments of Dallas, Tex.

Output Generator

As described in the device component of the Retinal Application, theencoder or encoders could drive many output elements. Several outputgenerator interfaces for driving target cells are possible.

For example, in some embodiments, the cells to be driven by the outputof the prosthetic 100 (i.e., the set C shown in FIG. 1A) may besensitized to light, e.g., using a light-activated transducer (such asChannelrhodopsin-2). The output generator 103 could be an LED array, aset of fiber optics driven by an LED, a digital light processing (DLP)device, among others.

These optical devices would output pulses of light that correspond tothe activity patterns of the cells in C. The pulses of light would drivethe light-activated transducer, causing the cells in C to fire as theencoder specifies. For example, the encoder would send signals to ageneral purpose input/output (GPIO), which would signal the LEDs.

For example, in some embodiments, an encoder's output is a set of spiketimes (times at which an action potential should be produced in thedownstream neuron). Because the output is in a sense binary (at eachmoment in time, a spike does or does not occur), this can be naturallyconverted into a program that sends high/low information to the GPIO.The GPIO then outputs voltage that is “high” and turns the LED on, or“low” and does not turn it on. In other words, the encoder produces aset of spike times, which get converted into TTL pulses through thesoftware and the GPIO, and pulses current then goes down a wire from theGPIO to the LED. The temporal resolution of the spike times produced bythe encoder may be sub-millisecond or any other suitable value.

The TTL pulses are the length of the neural signal (e.g., about 1 ms foran action potential.) In this example, the LEDs are separatelyaddressable (one for each encoder); however, other methods that allowbetter use of interface materials (data compression), such asmultiplexing or making use of correlations in the pulse patterns of theencoders to get many signals through to many LEDs rapidly, may be used.Finally, the addition of an amplifier to drive up signals to the LEDsmay be built in as well (to allow the neurons receiving the light pulsesto fire in a one-to-one manner or a near one-to-one manner with thepulses they receive).

For output generators based on electrodes, the output generator couldconsist of any device capable of driving current into the electrodes.

In general, as will be apparent to one skilled in the art, for variousapplications, any of the output generation techniques described in theRetinal Application may be adapted for use in the devices describedherein.

Exemplary Deployment of the Motor Prosthesis on a Human Subject

Referring to FIG. 8A, in one embodiment of the motor prosthetic 100,electrodes of the input receiver 101 are implanted in SMA. Theelectrodes and a battery pack are all subcutaneous, as in deep brainstimulation (DBS) methods used for Parkinson's patients. The batterypack to drive input receiver 101 is put in subcutaneously in theanterior chest wall; it has leads that are tunneled up to a site in thescalp so it can supply the needed power to the recording system.

The signals from the input receiver are sent wirelessly to the processor102, implemented in a unit worn on a belt with its battery pack.

The processor then drives output generator 103, as shown implemented asan implanted muscle stimulator system which is also completely internalto the human subjected including a power source. In some embodiments,the stimulator system may be of the type described in Guiraud et al,2006. In some embodiments, the dimensions of the stimulator arecomparable to the battery pack used for pacemakers (e.g., about 6 cm×6cm). In one embodiment, including the connectors to muscle, the width ofthe stimulator is about 10 cm. FIG. 8B shows an X-ray snapshot fromGuiraud et al, 2006, showing actual size of an exemplary stimulatingdevice inside a human.

Procedures for Measuring Motor Prosthetic Performance

The following describes exemplary procedures for measuring theperformance of the prosthetic 100 and its encoders. Performance of theencoders can be measured on a forced choice activity discrimination taskor performance on an error pattern test. The term “test stimulus” thatwill be used herein, refers to pattern of muscle activity, measuredusing EMG.

To evaluate performance on a forced choice discrimination task, a knowntest in the art, a confusion matrix is used (Hand D J. 1981). Aconfusion matrix shows the probability that a pattern of nerve branchactivity ({right arrow over (c)}, the population comprising theindividual activities of each subpopulation c_(i)) corresponds to itsappropriate pattern of SMA activity, {right arrow over (c)}_([k]). Togenerate different patterns of SMA activity, the animal (or human) isrequired to carry out an array of stereotyped movements (e.g., moving acursor to one of several locations on a computer monitor). Each kind ofmovement (for example, the movement to each location) is repeated formany trials, thus giving a set of SMA activities. For each movement typek, the set of SMA activities is denoted {right arrow over (a)}_([m]),and the set of resulting nerve branch activities is denoted {right arrowover (c)}_([k]).

With respect to the matrix, the vertical axis gives the movement type k.The horizontal axis gives the movement type predicted by decoding thepattern of nerve branch activity {right arrow over (c)}_([k]); thedecoded movement type is denoted m. The matrix element at position (k,m)thus gives the probability that nerve branch activity {right arrow over(c)}_([k]) is decoded as movement type m. If m=k, the nerve branchactivity pattern is decoded correctly, otherwise, it is decodedincorrectly. Put simply, elements on the diagonal indicate correctdecoding; elements off the diagonal indicate confusion.

To generate the confusion matrices, we divide the data into two sets: atraining and a testing set. The training set is obtained in order tobuild response distributions, and the testing set is obtained fordecoding.

To decode each pattern in the test set, {right arrow over (c)}_([k]), wedetermine the pattern of SMA activity that was the most likely to haveproduced it. That is, we determine the pattern {right arrow over(a)}_([m]) for which p ({right arrow over (a)}_([m])|{right arrow over(c)}_([k])) was maximal. Bayes' theorem is used, which states that p({right arrow over (a)}_([m])|{right arrow over (c)}_([k]))=p({rightarrow over (c)}_([k])|{right arrow over (a)}_([m]))p({right arrow over(a)}_([m]))/p({right arrow over (c)}_([k])), where p ({right arrow over(a)}_([m])|{right arrow over (c)}_([k])) is the probability that thepattern {right arrow over (a)}_([m]) in the SMA was present, given thatthe particular {right arrow over (c)}_([k]) was present in the nervebranches. p({right arrow over (c)}_([k])|{right arrow over (a)}_([m]))is the probability that a particular {right arrow over (c)}_([k])occurred given a particular {right arrow over (a)}_([m]), and p({rightarrow over (a)}_([m])) is the prior probability of {right arrow over(a)}_([m]). p({right arrow over (a)}_([m])) is set uniform in thisexperiment and so, by Bayes Theorem, p({right arrow over(a)}_([m])|{right arrow over (c)}_([k])) is maximized when p({rightarrow over (c)}_([k])|{right arrow over (a)}_([m])) is maximized. Whenp({right arrow over (a)}_([m])) is uniform, as it is here, this methodof finding the most likely pattern {right arrow over (a)}_([m]) given apattern {right arrow over (c)}_([k]) is referred to as maximumlikelihood decoding (Kass et al. 2005; Pandarinath et al. 2010; Jacobset al. 2009). For each occurrence of a movement type k that that wasdecoded as m, the entry at position (m,k) in the confusion matrix isincremented.

To build the distributions needed for the decoding calculations used tomake the confusion matrices (i.e., to specify p({right arrow over(c)}_([k])|{right arrow over (a)}_([k]))), the procedure is as follows.As mentioned above, the subject makes N types of movements (where N istypically 8), and each is repeated many times (e.g., >20 times). Foreach movement, we obtain a pattern of SMA activity {right arrow over(a)}_([k]), which we record via the implanted electrodes, and we obtaina pattern {right arrow over (c)}. Each pattern {right arrow over(a)}_([k]) is taken as the spike train spanning from ˜1 sec prior tomovement onset to ˜200 ms following movement onset, and binned with10-100 ms bins. Each pattern {right arrow over (c)}_([k]) is taken asthe nerve branch activity over the same period and binned in the sameway. In both cases, the spike generation process is assumed to be aninhomogeneous Poisson process, and the probability of any given patternof activity for the entire period is calculated as the product of theprobabilities for each bin. The probability assigned to each bin isdetermined by Poisson statistics, based on the training set response inthis bin. Note that this can be done by averaging over all trials for agiven type of movement pattern, or by considering each trialindividually.

Once the confusion matrices are calculated, overall performance in theforced choice activity discrimination task is quantified by “fractioncorrect”, which is the fraction of times over the whole task that thedecoded movement type m was correctly matched to the movement type k.

Given this procedure, at least 3 sets of analyses may be performed. Foreach one, the activity patterns from the normal subject are used for thetraining set and a different set of activity patterns is used for thetest set, as outlined below:

(1) The first set should consist of the test sets described above, i.e.,out-of-sample activity patterns from the normal subject. (These arerecordings of activity patterns in SMA and the nerve branches that werenot used to make the training set.) We use the fraction correct producedby the activity patterns from normal subjects as the baseline correctperformance.

(2) The second set should consist of the responses from the encoders.These are the responses {right arrow over (a)}_([k]) calculated from eq.1, from the recorded SMA activity patterns {right arrow over (a)}_([k]).Responses from this test set yield a measure of how well the encodersperform, given the training set response distributions used for analysis(1). The reason for performing the analysis this way is that we want tocompare the encoder's performance against the normal baseline condition.

When responses from the encoder are used as a test set, one obtains ameasure of how well the motor system would do with our proxy of thetransformation from SMA to the peripheral nerve branch activity (ourproxy of the motor system code).

(3) The third set, which is carried out only in subjects in which thenormal pathway from SMA to muscle has been damaged, is to determine theconfusion matrix that relates the movement actually made, to themovement that was intended. Since the normal pathways are damaged, themovement results from applying the prosthetic's encoder signals,determined as in analysis (2), to the muscles via the output generated(in this example, output uses electrodes, see above). The movementintended is determined from the subject's verbal responses, and can beverified by decoding the patterns of activity in SMA that are producedat the time of intention. This analysis provides a measure of how wellthe prosthetic performs after its output has been passed through to thereal tissue. This is a bottom-line measure of the prosthetic'sperformance in patients.

The encoder's performance and prosthetics performance in the forcedchoice discrimination task, as measured by “fraction correct”, will beat least about 35%, 50%, 60%, 70%, 80%, 90%, 95%, 99%, or 100% of theperformance of the normal system, or better than the normal system,measured as described above. Moreover, these performance levels may beobtained with response time for the prosthetic 100 which issubstantially the same as those found in an unimpaired subject. That is,in some embodiments, the prosthetic 100 in jumping impaired signalingcells introduces a lag time of which is of suitably short duration. Forexample, in some embodiments the lag time is less than a factor of 5, 4,3, 2, 1, 0.5, 0.1, (e.g., a factor in the range of 0.1-5 or any subrangethereof) or less times the signaling time exhibited by a normal subject.

Although a number of examples of neural prosthetic devices andtechniques have been presented above, it is to be understood thatnumerous modifications are possible.

For example, the above description of the strategy to find thetransformation to be implemented by the encoders; there are a number ofvariations that may be used.

In various embodiments, there are options for how spike trains (eitherinput from A or output to C) are represented. For example, they can berepresented as a point process in continuous time; they can be smoothedinto continuous rate functions, and they can be binned. In typicalembodiments, the data collected at both A and C is in the form of apoint process, but under some conditions it is easier to performoptimizations with smooth representations.

The smooth representations, then, can be reconverted to spike trains byassuming, for example, Poisson spike generation. Related to this, notethat some embodiments can also use a non-spiking measure to capture theneural activity in area A, such as a local field potential or opticallyrecorded signal. These represent a local average of neural activity, and(e.g., in circumstances that do not require resolution at the singleneuron level), may provide a more stable measurement. In these cases,the smooth representation of activity in A is used directly fordetermining the transformation.)

In various embodiments, there are options for the cost function to beused in optimization of the encoder transformation model. The examplespresented above use the likelihood, because it is well principled, butunder many circumstances, a mean-squared-error is an excellentapproximation and the optimization is faster to perform. Note, in regardto the previous paragraph, that in order to use mean-squared-error, someform of binning or smoothing is required.

In various embodiments, while the choice of a linear-nonlinear cascadeis a natural and principled one, other functional forms may also beapplicable, such as models with dynamic gain controls or neural networkmodels, or any transformation that can be expressed, explicitly orimplicitly, as a solution of a system of integral, differential, orordinary algebraic equations, whose form and coefficients are determinedby experimental data. This also includes models in which activity amongthe neurons in region C is correlated, e.g., via recurrent feedback.

Further, while in may cases it is most straightforward to fit the modelparameters for each neuron in A independently, in some applicationsthese parameters may have a systematic dependence on the neuron'slocation. Identification of this dependence will reduce the number ofindependent parameters that must be fit, and, potentially, allow forgeneralization of the model to neurons not actually recorded.

Also, it is notable that in embodiments where the prosthesis deviceperforms a jump to muscle, an involved extra transformation (e.g., fromSMA output to muscle response) is likely linear, so the cascade becomeslinear nonlinear linear (LNL) transformation to go from SMA to muscle.

Auditory Prosthesis

In several of the examples above, a prosthesis 100 is described which isused to restore or improve communication from one set of healthy cells Ato another set of health cells C by jumping a set of impaired signallycells B that separate the sets of healthy cells.

As noted above, in some embodiments, the input signal to the prosthesisis an external stimulus instead of the activity of the set of healthycells A. For example, FIG. 9 shows an auditory prosthetic 200. Theprosthetic 200 is a device to bypass damaged hair cells in the innerear, that is, to jump from sound stimuli directly to the output of thecochlea (the output of the spiral ganglion cells).

The prosthesis 200 includes an input receiver 201 for detecting an audiosignal (e.g., a microphone or other sound transducer) an converting theaudio signal to, e.g., a digital format. A processor 202 (sometimesreferred to herein as an encoder unit) processes the input signal fromthe input receiver 201 using a set of encoders to generate a set ofcoded outputs. An output generator 203 (e.g. an electrode or opticaldevice of the types described herein), in response to the coded outputs,activates auditory nerve cells (e.g., spiral ganglion cells) to producea response to the audio stimulus, e.g., a response that is substantiallythe same as the response in an unimpaired subject.

A well-functioning auditory prosthesis, e.g., one that can provide nearnormal or normal function in an impaired subject is advantageous becausethe incidence of hearing loss as the population ages is very high.

As in the examples presented above, an important aspect of theprosthetic 200 is the functioning of the encoders implemented by theprocessor 202. These are the components that carry out thetransformation from sound to cochlear output. As discussed above for themotor prosthetic and for the visual prosthetic described in the RetinalApplication, an advantage of this approach is that it has the capacityto generalize. It does this by using a mathematical transformation thatcaptures the relation between the outside world (in this case, audiostimuli) and the activity of a set of neurons. The techniques used hereare directly analogous to those used to generate the motor encodersdescribed above and visual encoders described in the RetinalApplication. The following discussion uses the notation developed hereinfor the motor encoders for convenience. However, one skilled in the artwill recognize that the formalism and techniques used in the RetinalApplication may be readily adapted to the present case of an auditoryprosthesis.

Again the approach for building the encoders is phenomenological: Onemay parameterize the relationship between the external stimuli and a setof neural signals or between two sets of neural signals, and find theparameter values using an optimization procedure, such as maximumlikelihood.

Note that in various embodiments, the prosthetic 200 uses signaling thatis not limited to frequency coding or intensity coding, but uses naturalcoding derived directly from data. That is, each encoder is essentiallya complete model for the input/output relations for a class of SG cell,where the input is the sound stimuli (such that the hair cells are beingjumped). This means it has the capability to transform any soundstimulus into the normal auditory output for that class of cell. Theencoders of the prosthesis 200 thus carry much more information thatsimple frequency detectors and transmitters (e.g., of the type describedin Boyden, 2010, U.S. Pat. Pub. No. 2010 0234273).

Constructing Auditory Encoders Using Experimental Data:

In some embodiments, encoders are constructed from data collected fromspiral ganglion (SG) neurons in an unimpaired subject while soundstimuli are presented. In some embodiments, one may implant an array ofextracellular electrodes e.g., using the techniques described in Sellick1982. Accordingly one obtain firing patterns from an array of SGneurons. At the same time, one may present sound stimuli. One mayformalize the relation between the sound stimuli and the SG responses as{right arrow over (c)}={right arrow over (f)} ({right arrow over (a)}),where {right arrow over (a)} is vector representing the sound (as a timeseries), and {right arrow over (c)} is the pattern of neural activity inthe SG neurons. Note that {right arrow over (a)} is univariate (it's avector where the components are sound (pressure) as a function of time)and {right arrow over (c)} is multivariate (as above, it represents theactivity of a population of neurons, the SG neurons). In someembodiments, the transformation may instead operate on the frequencyspectrum of the sound. As will be readily understood by one skilled inthe art, such a frequency spectrum may easily be obtained from {rightarrow over (a)} via a Fourier transform (e.g., performed by processor202 implementing an algorithm such as the well-known Fast FourierTransform).

To generate generalizable encoders, one may use the same strategydiscussed herein for generating the retinal encoders and the motorencoders. One may provoke the system with a broad range of stimuli. Inthe case of the retinal encoders, we presented the retinas from normalsubjects with two classes of stimuli—artificial (white noise) andnatural scenes—and recorded ganglion cell responses. We then modeled thetransformation from stimulus to response. The “training” stimuli (thewhite noise and natural scenes) were broad enough to produce a generalmodel, one that was effective on any stimulus. In other words, given thetraining stimuli, we obtained a model that faithfully reproducedganglion cell responses to essentially any stimuli (stimuli of arbitrarycomplexity).

Here, with the auditory system, one may take the same approach. On maypresent white noise (WN) and natural sound (NS) stimuli, where thelatter falls into two categories, environmental sound and sound relevantto language (both described in, for example, Lewicki, 2002.

Given the data sets generated in the previous step, one may model thetransformation between the sound stimuli and the SG responses. Thisprovides a set of encoders, e.g., one for each SG cell or correspondingto a small group of SG cells (e.g., containing less than 2, less than 3,less than 5, less than 10, less than 20, less than 30, less than 50, orless than 100 cells, e.g., in the range of 1-1000 cells or any subrangethereof).

As for the motor prosthetic, one may use the following parametric form,and determine the parameters of the form by optimizing a cost functionseparately for each SG neuron: for each SG neuron, c_(i), determineweight functions, {right arrow over (w)}_(i), and a nonlinearity, N_(i),so that the modeled transformation c_(i) ^(fit)=N_(i)({right arrow over(a)}·{right arrow over (w)}) is an optimal match to the actualtransformation, c_(i)=f_(i)({right arrow over (a)}). N_(i) is apointwise nonlinearity, i.e., a function y=N_(i)(x), where x and y areboth real-valued quantities (in the case of the retinal encoders, N_(i)was a cubic spline with 7 knots, but any suitable choice may be used),and {right arrow over (w)} is a vector of weights, specific to theoutput each SG neuron i. {right arrow over (w)}_(i) consists of an arrayof quantities w_(j)(t), where i labels a neuron in the SG population,and t is time. The ith component of the dot product {dot over (a)} iscalculated as follows:Σa(t)w _(i)(t)Note that this differs slightly from the parallel equation for the motorprosthetic in that it has no subscript j; this is because the quantity ahere is a one-dimensional function of time (or frequency in the casewhere an Fourier transform has been applied). As was the case for theencoders for the retina and motor systems, the optimization is performedto maximize the expected log likelihood over the entire outputpopulation, namely,

$L = \left\langle {\sum\limits_{i}\;{{ll}\left( {c_{i}^{fit},\overset{\rightarrow}{a}} \right)}} \right\rangle$ll(c_(i) ^(fit),{right arrow over (a)}) denotes the log likelihood thatc_(i) ^(fit) accounts for the observed activity of the ith neuron in SG,when {right arrow over (a)} is the sound input, and the brackets denotean average over all inputs. This likelihood is calculated from Poissonstatistics based on the model firing rates (i.e., c_(i) ^(fit)).

The weights {right arrow over (w)}_(i), i.e., the arrays w_(i,j)(t)correspond to a set of linear filters, one for each neuron i in the SG,and N_(i) is an adjustable nonlinearity for neuron i.

Exemplary Implementation of Auditory Prosthesis

Referring again to FIG. 9, the auditory prosthesis 200 may incorporateencoders built using the techniques described here, e.g., implemented bythe processor 202. The encoders are used in conjunction with an inputreceiver 201 (e.g., a microphone) and an output generator 203 whichstimulates a response in the SG cells.

As described herein, in various embodiments, the strategy is to firstdevelop encoders that capture the transformation from audio stimulus toSG activity (for arbitrary activity patterns), and, second, to use thecoded output these encoders to jump impaired cochlear hair cells anddirectly stimulate the SG cells to restore normal or near normalfunction.

In various embodiments, the output generator 203 may include anysuitable technology for stimulating SG neurons, such as that of the typedescribe in Zeirhofer et al., 1995 or Zeng et al, 2009. For example, inthe embodiment shown in FIG. 10A the prosthesis 200 works as follows: 1)a microphone included in the input receiver 201 sends signals to aprocessor 202, 2) the signal processor 202 converts the signals from themicrophone to signals to drive an array of electrodes in outputgenerator 203, and 3) the signals from processor 202 control theelectrodes that stimulate the SG neurons.

As shown, the microphone and a signal processing portion 202 a of theprocessor 202 are located outside of the subject. The signal processingportion 202 a generated coded outputs, and transfers them, e.g., via aradio frequency (RF) or other wireless link to a subcutaneouslyimplanted portion 202 a of the processor 202. The implanted portionreceiver the signal and controls the electrodes to stimulate the SGcells.

In other embodiments, all of the processing may occur externally, withan RF signal being used to directly drive implanted electrodes. Invarious embodiments other implementation schemed may be used. In someembodiments, an external power supply provides power to the subcutaneouselements, e.g., via an RF or inductive power coupling, or any otherpower transmission technique known in the art.

FIG. 10B shows a variant of the device of FIG. 10A, where the output ofthe encoders is sent not to electrodes, but to light emitting diodes(LEDs) included in the output generator 203 (or another light sources)to drive alternate transducers, e.g., channelrhodopsin-2 (ChR2) used tosensitive the SG cells. Pulses from the LEDs are used to drive aresponse in the sensitized SG cells.

In various embodiments, expression of ChR2 or other transducer genes inSG neurons can be achieved using the gene promoters described in Table 1of Liu et al, 2007. Examples include EF-1\alpha, NSE, CMV, CAG; theseall express in SG neurons. In various embodiments, any other suitablepromoters may be used.

With respect to delivery of the gene, any of the same gene therapyapproaches described in the Retinal Application can be used for deliveryto SG cells. Lentivirus (LV), adenovirus-5 (Ad-5) and adeno-associatedvirus-2 (AAV-2) have been shown to penetrate, although (Ad-5) was foundto be the most effective (under conditions where the round window of thecochlea, one of the openings to the inner ear, was left intact (Lei etal, 2010). If the round window is partially digested, then AAV-2 becomeseffective (Wang et al, 2011); this is valuable in some applications, asAAV-2 is one of the more promising gene therapy vectors in terms ofsafety (Simonelli et al, 2010). In various embodiments, any othersuitable delivery technique may be used.

Referring to FIGS. 11A and 11B, in some embodiments, the outputgenerator 203 includes a thin flexible LED array 1201 implanted in thecochlea 1202 of a subject. The flexible array is able to conform to thespiral shape of the cochlea, such that the LEDs may be positioned tostimulate SG cells. Note that although one possible configuration of thearray 1201 is shown, and other suitable positioning, array size, etc.

In some embodiments, the array 1201 includes an arrays ofinterconnected, ultrathin LEDs 1203 that are built into a flexiblewaterproof material. In various embodiments, the device can be placedinto the inner ear to stimulate the ChR2-expressing SG cells. In oneembodiment, each LED is 100 by 100 microns, which would stimulatemultiple cells; however, one can narrow its light path to target fewercells by masking a portion of the LED. In some embodiments, the size ofthe masking may be optimized to allow sufficient intensity to reach theChR2; “sufficient intensity” is defined as that which produces actionpotentials that follow the output of the encoder in a one-to-one or nearone-to one manner.

In some embodiments, the flexibility of the array 1201 matches well withthe curvature of the cochlea 1201: For example, in humans the radius ofcurvature of the cochlea ranges from 4 mm at the high frequency end to0.7 mm at the low frequency end, while in some embodiments, the radiusof curvature of the flexible device is e.g., 0.4 mm or less.

In some embodiments, the array 1201 may be of the type described in Kimet al, 2010. In various embodiments, the array 1201 may be operativelyconnected to the processor 202 using any suitable technique including,e.g., a wired or wireless connection.

In some embodiments, after device implantation, the encoder may beoptimized for the specific patient. Two examples of optimization are thefollowing. First, in some cases, different encoders capture differentinformation (e.g., frequencies, intensity), so they need to bepositioned on the SG neuron array to stimulate the appropriate SG cells(the SG cells that carry the same information). Second, in someembodiments, threshold levels and maximum levels have to be determined.This can be achieved using extracellular electrodes (e.g., using puretones to drive a small number of cells at a time).

Methods for Measuring Auditory Prosthesis Performance

The following describes exemplary procedures for measuring theperformance of the prosthetic 200 and its encoders. In some embodiments,the procedure for measuring the performance of the encoders and theprosthetic will follow directly from that used to test the retinalprosthetic or motor prosthetic, focusing specifically on performance ona forced choice discrimination task. The term “test stimulus” that willbe used herein, refers to a stimulus or a stimuli, which is presented toan animal for evaluation of performance of the encoders or encoders andoutput generator (e.g., the auditory prosthesis 200).

In various embodiments, it is important that the task used to measureprosthetic performance falls into a range of difficulty that allowsmeaningful information to be obtained. Briefly, the task must bedifficult enough (i.e. must use a stimulus set rich enough) that thenormal retinal responses provide information about the stimuli, but donot perform perfectly on the task. For example, in the task shown inExample 8 in the Retinal Application, the fraction correct using theresponses from the normal retina, was 80%, satisfying this criterion. Ifthe task used had been too hard, such that the normal retina'sperformance were near chance, then matching would have been of limiteduse to a performance analysis. Conversely, if the task chosen had beentoo easy (e.g., requiring just gross discriminations, such as blackversus white, and where the fraction correct for the responses from thenormal is near 100%), then prosthetic methods that are far fromapproximating the natural code and provide nothing close to normalvision would appear to do well. The same applies to the auditory tests:it is critical to use an appropriately challenging test, as was used inthe examples in the Retinal Application. The use of a challenging testalso allows one to determine if the prosthesis is performing better thanthe auditory system (i.e., entering into the domain of “bionichearing”).

Various methods for the forced choice task follow directly from thoseanalogous used in the Retinal Application, converting to auditorystimuli. Two types of natural stimuli may be used—natural environmentsound stimuli and speech-sound stimuli, as described in, for example,Lewicki, 2002. To evaluate performance on a forced choice discriminationtask, a known test in the art, a confusion matrix is used (Hand D J.1981). A confusion matrix shows the probability that a response to apresented stimulus will be decoded as that stimulus. The vertical axisof the matrix gives the presented stimulus (i), and the horizontal axisgives the decoded stimulus (j). The matrix element at position (i,j)gives the probability that stimulus i is decoded as stimulus j. If j=i,the stimulus is decoded correctly, otherwise, the stimulus is decodedincorrectly. Put simply, elements on the diagonal indicate correctdecoding; elements off the diagonal indicate confusion.

In this task, an array of stimuli is presented, specifically, stimulicontaining natural sounds, and the extent to which the stimuli can bedistinguished from each other, based on the responses of the SG cellsand/or encoders, is measured.

A training set is obtained in order to build response distributions (the“training set”), and another set is obtained to be decoded to calculatethe confusion matrix (the “test set”).

To decode the responses in the test set, one determines which of thestimuli s_(j) was the most likely to produce it. That is, one determinesthe stimulus s_(j) for which p(r|s_(j)) was maximal. Bayes theorem isused, which states that p(s_(j)|r)=p(r|s_(j))p(s_(j))/p(r), wherep(s_(j)|r) is the probability that the stimulus s_(j) was present, givena particular response r; p(r|s_(j)) is the probability of obtaining aparticular response r given the stimulus s_(j); and p(s_(j)) is theprobability that the stimulus s_(j) was present. p(s_(j)) is set equalfor all stimuli in this experiment and so, by Bayes Theorem, p(s|r_(j))is maximized when p(r|s_(j)) is maximized. When p(s_(j)) is uniform, asit is here, this method of finding the most likely stimulus given aresponse is referred to as maximum likelihood decoding (Kass et al.2005; Pandarinath et al. 2010; Jacobs et al. 2009). For eachpresentation of stimulus s_(i) that resulted in a response r that wasdecoded as the stimulus s_(j), the entry at position (i,j) in theconfusion matrix is incremented.

To build the response distributions needed for the decoding calculationsused to make the confusion matrices (i.e., to specify p(r|s_(j)) for anyresponse r), the procedure is as follows. The response r is taken to bethe spike train spanning 100 ms after stimulus onset and binned with 5ms bins; this is the appropriate timescale in particular for speechsounds. The spike generation process is assumed to be an inhomogeneousPoisson process, and the probability p(r|s_(j)) for the entire 100 msresponse is calculated as the product of the probabilities for each 5 msbin. The probability assigned to each bin is determined by Poissonstatistics, based on the average training set response in this bin tothe stimulus s_(j). Specifically, if the number of spikes of theresponse r in this bin is n, and the average number of spikes in thetraining set responses in this bin is h, then the probability assignedto this bin is (h^(n)/n!)exp(−h). The product of these probabilities,one for each bin, specifies the response distributions for the decodingcalculations used to make the confusion matrices.

Once the confusion matrices are calculated, overall performance in theforced choice visual discrimination task is quantified by “fractioncorrect”, which is the fraction of times over the whole task that thedecoded responses correctly identified the stimuli. The fraction correctis the mean of the diagonal of the confusion matrix.

Given this procedure, at east sets of analyses may be performed. Foreach one, the responses from the normal SG cells are used for thetraining set and a different set of responses is used for the test set,as outlined below.

(1) The first set may include or consist of responses from normal SGcells. This is done to obtain the fraction correct produced by normal SGcells.

(2) The second set may include or consist of the responses from theencoders (in various embodiments, the responses from the encoders, asindicated throughout this document and that of the original application,may be streams of electrical pulses, e.g., spanning 100 ms afterstimulus presentation, and binned with 5 ms, as are the normal SGresponses). In other embodiments, other suitable durations and bin timesmay be used.

Responses from this test set yield a measure of how well the encodersperform, given the response distributions of the normal SG cells. Thebasis for this is that the brain is built to interpret the responses ofthe normal SG cells (i.e., the naturally encoded responses.) Whenresponses from the encoder are used as a test set, one obtains a measureof how well the brain would do with our proxy of the normal SG responses(our proxy of the SG code).

(3) The third set may include or consist of responses from the SG cellsof a deaf animal or human driven by the encoders and output generator(e.g., driving a ChR2 based transducer), where the responses are of thesame duration and bin size as above. This set provides a measure of howwell the encoder performs after its output has been passed through toreal tissue.

As shown in Example 8 of the Retinal Application, the encoder'sperformance in the forced choice discrimination task was 98.75% of thenormal retina's performance, and complete system's performance, that is,the performance of an embodiment of the encoder, output generator, andrelated transducer was 80% of the normal retina's performance. Thus, forvarious embodiments, when tested in vitro or in an animal or humanmodel, the performance of the auditory prosthesis in the forced choicediscrimination task, as measured by “fraction correct”, should besimilar, that is at least about 35%, 50%, 60%, 70%, 80%, 90%, 95%, 99%,or 100% of the performance of the normal SG cells, or better than thenormal SG cells, measured as described above. Moreover, theseperformance levels may be obtained with response time scales for theprosthetic 200 which are substantially the same as those found in anunimpaired subject. That is, in some embodiments, the prosthetic 200 injumping impaired cochlear hair cells introduces a lag time of which isof suitably short duration. For example, in some embodiments the lagtime is less than a factor of 5, 4, 3, 2, 1, 0.5, 0.1, (e.g., a factorin the range of 0.1-5 or any subrange thereof) or less times thesignaling time exhibited by a normal subject.

Other Embodiments

Although several examples have been provided, it is to be understoodthat numerous variations are within the scope of the present disclosure.For example, although prostheses for auditory and motor applicationshave been provided, it is to be understood that the devices andtechniques may be applied in a variety of additional settings. Further,although various examples of cell and tissue types have been provided(e.g. jumping from SMA to SMN or muscle, or jumping from an audiostimulus to SG), it is to be understood that other types of cells,tissue, etc. may be used. In general, the devices and techniquesdescribed herein may be adapted to a wide variety of cases where aprosthetic is required which operates as a proxy for signaling cellswhich have suffered some form of gap or impairment.

Tables 2-6 summarize a number of applications where the devices andtechniques described herein may be used to restore or improve function.For each application, the tables set forth a region of the nervoussystem that is impaired, the resulting body parts that have diminishedfunction, the cause of the injury or impairment, the region from whichactivity is read (corresponding to A in FIG. 1B), the region which isstimulated (corresponding to C in FIG. 1B), and the connection that usbypassed or “jumped.” It is to be understood that the examples providedin the tables are in no way exhaustive.

TABLE 2 Body Part(s) Region of That Have CNS That is Diminished Cause ofImpaired Function Impairment Input Region Output Region Connectiondorsal column impairment of tabes dorsalis dorsal root (medial primarytract aka procrioception, (sensory or: right lemniscus) somaticposterior/dorsal vibratory ataxia); before VPL sensory horn (dorsalsensation/loss stereoanethesia lesioned part thalamus cortex whitecolumn) of deep tendon (impaired of tract; or: right after (postcentralfibers reflex (skin, graphesia and Adams' and lesioned part gyrus);joints, tendons); tactile Victor's of tract; Waxman, 56; impaired two-localization); Neurology Ch Waxman 57; http://www. point multiple 9http://www. ncbi.nlm.nih. discrimination; sclerosis, ncbi.nlm.nih.gov/books/N figure writing; vitamin B12 gov/books/N BK11142/;; detectionof deficiency, HIV BK11142/ Brazis 287 size, shape, and human T- weight,and lymphotropic texture of virus infection; objects; ability Waxman 68;to detect the Ropper and direction and Samuels ch 9; speed of a movingstimulus on the skin; Waxman 68, 55, 56, 57; Ropper and Samuels Ch 9Spinothalamic (skin) loss of Syringomyelia; posterior root (medialprimary Tract pain/temp stroke; trauma; ganglion axons lemniscus)somatic (ventrolateral sensation Waxman 66, 68; aka dorsal root VPLsensory column fibers) below/opposite Kierman 77; or: right thalamuscortex side of lesion http://www.nc before or: right after (postcentral(ipsilateral lower bi.nlm.nih.gov/ lesioned part lesioned part gyrus);extremities); pmc/articles/P of tract; of tract; Waxman 57; motorMC2170182/?t Snell 142; Waxman 56; http://www. weakness same ool=pubmed;Waxman Ch 5 http://www. ncbi.nlm.nih. side of lesion; http://www.nc SecIII; ncbi.nlm.nih. gov/books/N ipsilateral side bi.nlm.nih.gov/gov/books/N BK10967/; of face; pubmed/14663 BK10967/; Brazis 287neuronal 044 Brazis 287 hyperexcitability at injury/above the injury;pain below the injury level (central pain); Waxman 56; http://www.ncbi.nlm.nih.gov /books/NBK109 67/; Brazis 370; http://www.ncbi.nlm.nih.gov/pm c/articles/PMC2 170182/?tool=p ubmed; www.ncbi.nlm.nih.gov/p ubmed/1466304 4 Dorsal muscle X-Chromosome posteriorroot precerebellar inferior Spinocerebellar spindles/Golgi Linked Copperaka dorsal root nuclei cerebellar tract aka tendon Malabsorption;(posterior gray or: right after peduncle; posterior organs, touch +Hereditory column) lesioned part Kierman spinocerebellar pressurereceptors Spastic or: right of tract; 72, 167; 2) tract (lateral vianucleus Paresis; spinocer- before Kierman 93; http://www. column fibers)dorsalis; ebellar ataxia lesioned part http://www. accessmediciipsilateral lower (atrophy + of tract; dartmouth.e ne.com/contextremities demyelinization Snell 147 du/^(~)rswenso ent.aspx?aID(vibration/posi- of fibers); Miller n/NeuroSci/c =5272458&s tionalsensory Fisher-Guillain hapter_7A.ht earchStr=cer functions); BarreOverlap ml ebellar+pedu severe Syndrome; ncle#527245 ophthalmoplegiahttp://onlinelib 8 (paralysis of rary.wiley.com/ eye muscles),doi/10.1002/an bilateral a.410050609/a ptosis(eyelid), bstract;areflexia, http://www.sci and moderate encedirect.com cerebellar/science/article ataxia; /pii/0022510X9 irresponsive 490037X; (SCApupils; facial 2) nerve palsy; http://www.nc Waxman 56; bi.nlm.nih.gov/Brazis 370; pubmed/14507 http://cornell.w 334; orldcat.org/title/http://www.nc position-and- bi.nlm.nih.gov/ vibration- pubmed/78768sensations- 62 functions-of- the-dorsal- spinocerebellar-tracts/oclc/1147 67304&referer= brief_results; http://www.ncbi.nlm.nih.gov/pu bmed/7876862 Ventral 1)muscle a) Miller Fisher- dorsalroot precerebellar superior Spinocerebellar spindles/Golgi GuillainBarre ganglion axons nuclei cerebellar tract aka tendon organs Overlap(posterior gray or: right after peduncle ((to anterior (sensory inputSyndrome; column) lesioned part cerebellar spinocerebellar from skeletalb) Friedrich's or: right of tract; cortex); tract muscle), Syndromebefore Kierman 93; Kierman 72; touch + pressure (heredo-ataxia);lesioned part http://www. http://www. receptors; 2) a) of tract;dartmouth.e accessmedici severe http://www.nc Snell 146 du/^(~)rswensone.com/cont ophthalmoplegia bi.nlm.nih.gov/ n/NeuroSci/c ent.aspx?aID(paralysis of pubmed/78768 hapter_7A.ht =5272458&s eye muscles), 62; mlearchStr=cer bilateral b) ebellar+pedu ptosis(eyelid), http://www.ncncle#527245 areflexia, bi.nlm.nih.gov/ 8 and moderate pubmed?term=cerebellar %22ventral%20 ataxia; spinocerebellar irresponsive%20tract%22%2 pupils; 3) facial 0ataxia nerve palsy; optic nervedegeneration; 1) Waxman 56; http://www.blac kwellpublishing.com/patestas/c hapters/10.pdf; 2) http://www.ncbi .nlm.nih.gov/pubmed/7876862; 3) http://www.ncbi .nlm.nih.gov/pu bmed?term=%22ventral%20spin ocerebellar%20t ract%22%20atax ia Spinoreticular deepsomatic Wallenberg's posterior root reticular Thalamus; Tract (lateralstructures; lack Syndrome; ganglion axons formation cerebral column) oftriggering of http://www.nc or: right (precerebellar cortex; noxiousbi.nlm.nih.gov/ before nucleus) http://www. inhibitory pubmed?term=lesioned part or: right after blackwellpub controls Diffuse%20noxi oftract; lesioned part lishing.com/p (nonpainful but ous%20inhibito Snell150 of tract; atestas/chap noxious stimuli); ry%20controls% http://www.ters/10.pdf; hemianalgesia; 20in%20man.% accessmedici Latash 171 Waxman56; 20Involvement ne.com/cont (Neurophysio http://www.ncbi %20of%20the%ent.aspx?aID logical basis .nlm.nih.gov/pu 20spinoreticula =5271956&s ofbmed?term=Diff r%20tract earchStr=spi movement) use%20noxiousnocerebellar %20inhibitory% +tracts#5271 20controls%20in 956;%20man.%20Inv Kierman 72; olvement%20of http://www. %20the%20spinsciencedirect oreticular%20tra .com/science ct /article/pii/S 0301008298000483 Corticoponto- myelin decay ataxic nerve cells in pontinecerebellar cerebellar (white matter neurodegerena- frontal/parietal/nuclei cortex; Pathway tracts); tive diseases temporal/oc- or: rightafter Snell 226-229 (pontocerebellar dysarthria (hereditary cipitallobes of lesioned part tract; (mouth), spinocerebellar cerebral oftract; pontine nuclei; hemiparesis of ataxia); multiple cortex Snell226- part of one side, system atrophy or: right 229 cerebellum)nystagmus (MSA); late- before (involuntary eye onset cerebellar lesionedpart twitching); cortical atrophy of tract; http://www.ncbi (LCCA);stroke; Snell 226-227 .nlm.nih.gov/pu http://www.nc bmed/18172629bi.nlm.nih.gov/ pubmed/18172 629; http://www.nc bi.nlm.nih.gov/pubmed/83421 90 cerebro- involuntary eye olivocerebellar nerve cells ininferior cerebellar olivocerebellar twitching atrophy; frontal/parietal/olivary nuclei cortex; tract fibers (rebound cerebellar temporal/oc- or:right after Snell 229 nystagmus), ataxia; cipital lobes of lesioned partwasting of small http://www.nc cerebral of tract; muscles of bothbi.nlm.nih.gov/ cortex Snell 229 hands, spastic pubmed/79314 or: rightparalysis of both 42; before legs, lesioned part dysdiadochoki- oftract; nesia (lack of Snell 226 coordination)of upper limbs, oculardysmetria; http://www.ncbi .nlm.nih.gov/pu bmed/7931442;

TABLE 3 Body Part(s) Region of That Have CNS That is Diminished Cause ofImpaired Function Impairment Input Region Output Region ConnectionVentromedial ipsilateral Kierman 1) medial inferior medulla hypoglossal108, 109; dorsomedial lemniscus; cerebellar palsy (tongue Head and neckhypothalamus Waxman 86 peduncle paralysis); surgery-- neurons (cerebralcontralateral otolaryngology 2) midbrain cortex); hemiplegia/ By ByronJ. periaqueduc- Waxman 86; hemiparesis; loss Bailey p119; tal gray (forSmith et al of sense of Jonas T. rostral 45 temp/pain Johnson, Shawnventromedial (skin); D. Newlands; medulla); Kierman 108;http://stroke.ah 1) http://www.scie ajournals.org/co http://www.nncedirect.com/s ntent/26/4/702. cbi.nlm.nih.go cience/article/pi full;v/pubmed/21 i/S10523057988 http://www.scie 196160 0027X; ncedirect.com/s2) http://www.nej cience/article/pi http://www.a m.org/doi/full/1i/S03064522060 nnualreviews. 0.1056/ENEJMic 03836; org/doi/abs/1m020058; http://www.scie 0.1146/annur http://www.scie ncedirect.com/sev.ne.14.0301 ncedirect.com/s cience/article/pi 91.001251cience/article/pi i/S10523057988 i/S10523057988 0027X 0027X;http://archneur. ama- assn.org/cgi/rep rint/57/4/478 Lateral Medulla 1.ipsilateral Wallenberg's solitary tract medial inferior palate paralysissyndrome nucleus (NTS); lemniscus; cerebellar (roof of mouth); “Lateralhttp://www.s Waxman 86 peduncle vocal cord Medullary ciencedirect.c(cerebral paralysis; loss of Syndrome” om/science/a cortex); pain/heat(vertigo, ataxia); rticle/pii/S105 Waxman 86; sensation on caused by38119080100 Smith et al same side of inferior artery 1X; 45face/opposite of occlusion; http://onlineli body (skin?); trauma;stroke; brary.wiley.co loss of facial Kierman 107, m/doi/10.100 sweating(skin); 108, 109; 2/cne.21105/ 2. diminishment http://www.spri abstractpf pharyngeal ngerlink.com/co reflex (pharynx); ntent/p7662218 limbweakness; 4414hr60/; Kierman Waxman Ch 7 108, 110; Clinicalhttp://keur.eldo Illustration 7-1 c.ub.rug.nl/FILES /wetenschappers/1/478/478.pdf; http://stroke.ah ajournals.org/co ntent/28/4/809.abstract; Brazis 369; http://www.spri ngerlink.com/co ntent/f348889372351m38/ Lateral Medulla ipsilateral plate Avellis' solitary tractmedial inferior paralysis; vocal syndrome; nucleus lemniscus; cerebellarcord paralysis; dysphagia; acute (NTS); Waxman 86 peduncle loss ofpain/heat stroke; http://www.s (cerebral on ipsilateral Kierman 108;ciencedirect.c cortex); side of face/ http://www.ncbi om/science/aWaxman 86; contralateral .nlm.nih.gov/pu rticle/pii/S105 Smith et alside of body bmed/8821503; 38119080100 45 (face-arm-trunk-http://www.ncbi 1X; legs); .nlm.nih.gov/pu http://onlineli Kierman 108;bmed/21576937 brary.wiley.co http://www.ncbi m/doi/10.100.nlm.nih.gov/pm 2/cne.21105/ c/articles/PMC2 abstract 170182/pdf/v065p00255.pdf; http://jnnp.bmj. com/content/65 /2/255.abstract ponsipsilateral LMN Millard Gubler's midbrain pontine middle (corticospinalparalysis syndrome; basis nuclei; cerebellar fibers/descending (face);contralat- trauma; pedunculi Kierman 101; peduncle fibers) eralhemiplesia; Kierman or: Smith 56 (cerebellum); or: undamaged 108;localization undamaged Kierrman 101 fibers before the in clinical partof fibers Wxman 89; lesion; neurology by right after Brazis et alKierman 108; braxis/masdeu/ lesion; 357 localization in biller 291;Kierman 101 clinical http://content.k neurology by arger.com/Prodbraxis/masdeu/ ukteDB/produkt biller 291, 553; e.asp?Aktion=Shhttp://content.k owPDF&ArtikelN arger.com/Prod r=000116965&AukteDB/produkt usgabe=234289 e.asp?Aktion=Sh &ProduktNr=22owPDF&ArtikelN 3840&filename= r=000116965&A 000116965.pdf usgabe=234289&ProduktNr=22 3840&filename= 000116965.pdf dorsal pons ipsilateral LMNFoville's pontine middle (pontine facial paralysis Syndrome nuclei;cerebellar tegmentum) (face); ipsilateral (lower dorsal Kierman 101;peduncle conjugate gaze pontine Smith 56 (cerebellum); paralysis (eyes);syndrome); Kierrman contralateral Wall-Eyed 101; hemiparesis;Internuclear Waxman 89; blepharospasm Ohtalmoplegia Brazis et al (eyelidclosing); WEBINO 357 motor tract syndrome damage; facial (caused bynerve damage; stroke; multiple failure to abduct schlerosis; eye;infections); Kierman stroke; 108, 110; Kierman http://keur.eldo 108,110, 111, 121; c.ub.rug.nl/FILES http://stroke.ah /wetenschapperajournals.org/co s/1/478/478.pdf; ntent/11/1/84.a http://stroke.ahbstract; Brazis et ajournals.org/co al 359; ntent/28/4/809.http://www.spri abstract; ngerlink.com/co Brazis 369; ntent/f3488893http://www.spri 72351m38/; ngerlink.com/co http://www.ncbintent/f3488893 .nlm.nih.gov/pu 72351m38/ bmed/21729278 ventral ponsipsilateral Raymond's pontine middle (pontocerebellar abducens nerveSyndrome; nuclei cerebellar fibers) palsy (VI nerve, Locked in neurons'peduncle lateral rectus Syndrome axons (cerebellum) muscle of eye);(caused by (cerebral or: contralateral Stroke or cortex) undamagedhemiparesis (½ traumatic brain or: portion of of body); upper injury dueto undamaged pontocerebellar motor neuron obstructed portion of fibersquadriplegia, basilar artery); pontocerebellar right after paralysis ofanarthria fibers right the lesion; lower cranial (speech loss); beforethe Kierman 101 nerves, quadriplegia; lesion; Waxman 89; bilateralparesis Kierman 108; Kierman 101; Brazis et al. of horizontalhttp://www.spri Smith 56 357 gaze; ngerlink.com.pr Kierman 108;oxy.library.corne http://stroke.ah ll.edu/content/7 ajournals.org/co4n878271705ru ntent/28/4/809. 11/; abstract; http://www.ncbihttp://www.ncbi .nlm.nih.gov/pu .nlm.nih.gov/pu bmed/12119076bmed/12119076 cerebral ipsilateral Benedikt's lenticular Pontine medullapeduncle oculomotor Syndrome; nucleus aka Nuclei; oblongata; (pyramidalabducens nerve Weber's corpus Kahle and Morris and fibers/fascicle palsy(pupil of syndrome (i.e. striatum Frotscher McMurrich of cranial nerveeyes); Ventral externus 166; 876 3) contralateral Midbrain (olfactoryMorris and hemiparesis; Syndrome); lobe fasciculi) McMurichcontralateral peduncular or: 871 hemiplegia hallucinosis (for unlesioned(face); tremor + vascular part involuntary lesions); stroke; Stricker416 movements (red Dysarthia nucleus (Clumsy Hand destruction);Syndrome); heaviness of Kierman 108; limbs/difficulty http://www.harrusing isonspractice.co hand/slurred m/practice/ub/v speech (disorderiew/Harrisons% of articulatory 20Practice/1416 movements of11/all/Double+V tongue + oris ision; http://ww muscles);w.ncbi.nlm.nih.g unwanted hand ov/pubmed/188 activity; 26349 Kierman108; http://www.brig http://onlinelibr hamandwomens ary.wiley.com/d.org/Departmen oi/10.1002/mds. ts and Services 10084/full;/neurology/servi http://www.ncbi ces/NeuroOphth .nlm.nih.gov/puamology/Images bmed/18826349; /SelectedPublica http://www.brigtions/Strabismu hamandwomens s.pdf: .org/Departmen Brazis 361, 362;ts_and_Services http://www.ncbi /neurology/servi .nlm.nih.gov/puces/NeuroOphth bmed?term=Gel amology/Images ler%20TJ%2C%2/SelectedPublica 0Bellur%20SN.% tions/Strabismu 20Peduncular%2 s.pdf;0hallucinosis%3 http://www.scie A%20magnetic% ncedirect.com/s20resonance%2 cience/article/pi 0imaging%20co i/S08872171019nfirmation%20of 00034; %20mesenceph Brazis 361, 362; alic%20infarctioTheime's n%20during%20l Anatomic Basis ife.%20Ann%20 of NeurologicNeurol%201987 Diagnosis Atlas %3B21%3A602% 226; E2%80%93604;http://www.ncbi http://www.ncbi .nlm.nih.gov/pm .nlm.nih.gov/puc/articles/PMC1 bmed/17621531 073816/ http://www.scie ncedirect.com/science/article/pi i/S10523057080 01535; http://w ww.ncbi.nlm.nih.gov/pmc/article S/PMC1073816/ dorsal conjugate Parinaud's occipital a)caudal a) Thalamus; midbrain upward gaze syndrome (aka cortex nucleus;b) primary (superior paralysis w-o dorsal midbrain (corticotectal b)lateral visual cortex; colliculus, paralysis of syndrome, fibers);geniculate Westerlain pretectal area, convergence; pretectal Kierman102- nucleus 248; posterior abnormalities of syndrome, 103 (LGN);http://www. commisure etc) pupil response Sylvian http://www.ncbi.nlm.nih. (eyes); paralysis aqueduct ncbi.nlm.nih. gov/pubmed ofvertical gaze; syndrome); gov/pubmed /21344403 ipsilateral head tumorpressure /21344403 tilt; vertical on posterior diplopia commissure/(downwards/co pretectal ntralesional area/superior gaze); colliculi;Kierman 108, trauma; stroke; 121; Horner's http://www.ncbi Syndrome;.nlm.nih.gov/pu miningitis/herpes bmed/20182210; zoster/syphilishttp://www.scie (connective ncedirect.com/s tissue cience/article/piinfections); i/S03038467090 Kierman 02406; 108, 121; http://stroke.ahajournals.org/co ntent/12/2/251. abstract; http://www.ncbi.nlm.nih.gov/pu bmed/20182210; http://www.scie ncedirect.com/science/article/pi i/S03038467090 02406 Middle ipsilateral facialanterior inferior pontocerebellar Cerebellum; cerebellar paralysis(face), cerebellar artery fibers Young et al peduncle aka impairedfacial (AICA) injury; (from pontine 105 branchial sensation (skin);lateral inferior nuclei pontis paralysis of pontine neurons' conjugategaze syndrome; axons); to the side of ataxia; Kierman 101 the lesionaneurysm; (eyes); stroke; cardiac contralateral embolism; sense loss oftrauma; temp/pain; localization in deafness (ears); clinical tinnitus(ears); neurology by middle braxis/masdeu/ cerebellar biller 553;peduncle http://www.ncbi infarction .nlm.nih.gov/pu (nystagmus,bmed/21748288; speech http://www.ncbi difficulty, ataxia .nlm.nih.gov/puof limbs/trunk); bmed/20572906; inner ear http://www.nc dysfunctionbi.nlm.nih.gov/p (vertigo/tinnitus/ ubmed/1983486 bilateral 5; hearingloss); http://www.ncbi (anterior inferior .nlm.nih.gov/pu cerebellarbmed/21631321 artery-related) localization in clinical neurology bybraxis/masdeu/ biller 553; http://stroke.ah ajournals.org/content/33/12/28 07.full; http://brain.oxf ordjournals.org/content/113/1/1 39.abstract?ijke y=60f163a9bdc3 3efe496746bc1effc8f9c4e1dd9c &keytype2=tf_ip secsha; http://www.ncbi .nlm.nih.gov/pubmed/20572906; http://www.nc bi.nlm.nih.gov/p ubmed/1983486 5;http://www.n cbi.nlm.nih.gov/ pubmed/197971 77

TABLE 4 Body Part(s) Region of That Have CNS That is Diminished Cause ofImpaired Function Impairment Input Region Output Region Connection C2root impairment of tumors; dorsal spinothalamic periaquaductalrespiratory http://www.ncbi rami/afferent tract, grey function;.nlm.nih.gov/pu fibers from spinomesence- (midbrain); Currrentbmed/21123996 dorsal root phalic tract; thalamus; Treatment and ganglionhttp://www. http://www. Diagnostic in or: right ncbi.nlm.nih.ncbi.nlm.nih. Orthopedics ch before the gov/pubmed gov/pubmed 13lesioned part /2358537 /2358537 of the root; (for cervical (for cervicalKierman 62; enlargement enlargement Waxman 48- projections projections49 in general); in general); Thieme Color Thieme Color Atlas of theAtlas of the Human Body, Human Body, p558- p558- 559(reference559(reference for cervical for cervical enlargement enlargementcomponents) components) C3 root jaw/neck; sensory dorsal 1) Ventral 1)infrahyoids, disturbances; rami/afferent Spinocerebellar cerebellumsemispinalis muscle paresis; fibers from Tract; 2) capitis and (trauma)dorsal root 2) periaquaductal cervicis, subluxation of ganglionspinothalamic grey longissimus spinal axis; or: right tract, (midbrain);capitis and degenerative before the spinomesence- thalamus; cervicis,motor root C3 lesioned part phalic tract; 1) intertransver- compressionof the root; 1) http://www. sarii, rotatores, (ventral osseus Kierman62; http://www. ncbi.nlm.nih. multifidi compression); Waxman 48-ncbi.nlm.nih. gov/pubmed muscle Brazis et al 93; 49 gov/pubmed/14337566?d paresis; diapragm http://www.ncbi /14337566?d opt=Abstractweakness/ .nlm.nih.gov/pu opt=Abstract &holding=np anteriorbmed/21120549 &holding=np g; trunk; g; http://www. Brazis et al 93;2)http://ww ncbi.nlm.nih. waxman 51 w.ncbi.nlm.ni gov/pubmed h.gov/pubme/2358537 d/2358537 (for cervical (for cervical enlargement enlargementprojections projections in general); in general); Thieme Color ThiemeColor Atlas of the Atlas of the Human Body, Human Body, p558- p558-559(reference 559(reference for cervical for cervical enlargementenlargement components); components) 2) http://www.s ciencedirect.com/science/ article/pii/S0 0068993980 04120 (for cuneate nucleus ingeneral); Thieme Color Atlas of Human Anatomy Vol III - Nervous Systemand Sensory Organs 341 (for cuneate nucleus- thalamus- cortexconnection) Thieme Color Atlas of the Human Body, p558- 559(referencefor cervical enlargement components) C4 root scalene/levator muscleparesis; dorsal spinothalamic 1) scapulae/ degenerative rami/afferenttract, periaquaductal trapezoid motor root C4 fibers from spinomesence-grey (shoulder)/rhom- compression dorsal root phalic tract; (midbrain);boid muscles (ventral osseus ganglion 1) thalamus paresis; compression);or: right http://www. 2) diaphragmic trauma/birth before thencbi.nlm.nih. postcentral paresis + injury; trauma; lesioned partgov/pubmed cyrus (from pulmonary compression by of the root; /14337566?dcuneate difficulty; a ganglion; Kierman 62; opt=Abstract nucleus todiaphragm Brazis et al 93; Waxman 48- &holding=np thalamus); weakness/http://www.ncbi 49 g; 1) anterior trunk; .nlm.nih.gov/pu 2)http://wwhttp://www. Brazis et al 93; bmed/21120549 w.ncbi.nlm.ni ncbi.nlm.nih.waxman 51 h.gov/pubme gov/pubmed d/2358537 /14337566?d (for cervicalopt=Abstract enlargement &holding=np projections g; in general);http://www. Thieme Color ncbi.nlm.nih. Atlas of the gov/pubmed HumanBody, /2358537 p558- (for cervical 559(reference enlargement forcervical projections enlargement in general); components) Thieme ColorAtlas of the Human Body, p558- 559(reference for cervical enlargementcomponents); 2) http://www.s ciencedirect. com/science/ article/pii/S00068993980 04120 (for cuneate nucleus in general); Thieme Color Atlas ofHuman Anatomy Vol III - Nervous System and Sensory Organs 341 (forcuneate nucleus- thalamus- cortex connection) Thieme Color Atlas of theHuman Body, p558- 559(reference for cervical enlargement components) C5root neck/shoulder/ depressed bicets dorsal spinothalamic 1) upperreflex; rami/afferent tract, periaquaductal anterior arm depressedfibers from spinomesence- grey pain; sensory brachioradialis dorsal rootphalic tract; (midbrain); disturbances reflex; cervical ganglionhttp://www. thalamus on lateral arm; spondylosis(de- or: rightncbi.nlm.nih. 2) muscle paresis generative tissue before the gov/pubmedpostcentral for levator of cervical lesioned part /2358537 cyrus (fromscapulae, vertebrae); of the root; (for cervical cuneate rhomboids,cervical Kierman 62; enlargement nucleus to serratus radiculopathy;Waxman 48- projections thalamus); anterior, post-operative 49 ingeneral); http://www. supraspinatus, (decompression/ Thieme Colorncbi.nlm.nih. infraspinatus, spinal cord Atlas of the gov/pubmeddeltoid, fusion) C5 palsy Human Body, /2358537 biceps, following p558-(for cervical brachioradialis; anterior 559(reference enlargementdiaphragmatic decompression for cervical projections paresis (if andspinal fusion enlargement in general); damaged C5 for cervicalcomponents); Thieme Color fibers reach degenerative http://www.s Atlasof the phrenic diseases; ciencedirect. Human Body, nerve); contributingpre- com/science/ p558- biceps/brachio- existing article/pii/S0559(reference radialis (poor asymptomatic 0068993980 for cervicalreflex); damage of the 04120 enlargement hemidiaphragmic anterior horncomponents) paresis + cells at C3-C4 pulmonary and C4-C5 levelsdifficulty; (motor radicular pain weakness); (suprascaular upperbrachial region of plexus palsies; root); deltoid high velocityweakness; impact (like Brazis et al 93; football) causing http://www.jonerve avulsion; sonline.org/ab trauma; stracts/v18n3/ compression by356.html; a ganglion; Waxman 51 Brazis et al 93; Frank 1031;http://www.joso nline.org/abstrac ts/v18n3/356.ht ml; http://www.ncbi.nlm.nih.gov/pu bmed/20461418; http://www.scie ncedirect.com/science/article/pii /S036350231000 5101; http://www.ncbi .nlm.nih.gov/pmc/articles/PMC2 504282/; Theime Atlas of Neurology 767- 768 C6 rootlateral/dorsal hyperflexia (if dorsal 1) n/a 1) forearm pain;corticalspinal rami/afferent 2) Ventrolateral paresis of tract isdamage); fibers from Spinothalamic Medulla muscles depressed dorsal roottract (VLM) Nuclei; (erratus biceps/brachio- ganglion (dorsal Solitarytract anterior, radialis reflex (due or: right column); nucleus biceps,to compression before the 1) n/a (NTS), lateral pronator teres, of C5-6vertebral lesioned part 2) reticular flexor carpi level); cervical ofthe root; http://www.s nucleus (LRt), radialis, spondylosis(de- Kierman62; ciencedirect. caudal/rostral brachioradialis, generative tissueWaxman 48- com/science/ ventrolateral extensor of cervical 49article/pii/S0 medulla; carpi radialis vertebrae); 0068993980 2) longus,cervical 04120 postcentral supinator, and radiculopathy; cyrus (fromextensor carpi upper brachial cuneate radialis brevis); plexus palsies;nucleus to depressed ipsilateral root thalamus); biceps/brachio- injury;C5-C6 1) radialis reflex; unilateral facet http://www.s radicular paindislocation ciencedirect. (posterior (vertebrae injury com/science/deltoid due to trauma article/pii/S1 region); biceps like car 5660702020weakness; accident); high 00346; Brazis et al 93; velocity impact 2)http://www.jo (football) http://www.s sonline.org/ab causing nerveciencedirect. stracts/v18n3/ avulsion; com/science/ 356.html; trauma;article/pii/S0 Waxman 51 compression by 0068993980 a ganglion; 04120(for Brazis et al 93; cuneate Frank 1031; nucleus in http://www.josogeneral); nline.org/abstrac Thieme Color ts/v18n3/356.ht Atlas of ml;Human http://www.scie Anatomy Vol ncedirect.com/s III - Nervouscience/article/pii System and /S036350231000 Sensory 5101; Organs 341Johnson Ch 29 (for cuneate (Principles of nucleus- Critical Care);thalamus- http://www.ncbi cortex .nlm.nih.gov/pm connection)c/articles/PMC2 504282/ C7 root pain in dorsal compression due dorsal 1)n/a 1) forearm/deep to disc rami/afferent Ventrolateral breast;herniation at C6- fibers from Medulla sensory 7 vertebral level; dorsalroot (VLM) Nuclei; disturbances cervical ganglion Solitary tract on3rd/4th osteoarthritis; or: right nucleus digits; paresis cervicalbefore the (NTS), lateral of muscles spondylosis lesioned part reticular(serratus (degenerative of the root; nucleus (LRt), anterior, tissue ofcervical Kierman 62; caudal/rostral pectoralis vertebrae); Waxman 48-ventrolateral major, cervical 49 medulla; latissimus radiculopathy; 1)dorsi, pronator upper brachial http://www.s teres, flexor plexuspalsies; ciencedirect. carpi radialis, trauma; com/science/ triceps,Brazis et al 94; article/pii/S1 extensor carpi Frank 1031; 5660702020radialis longus, http://www.joso 00346; extensor carpi nline.org/abstracradialis ts/v18n3/356.ht brevis, extensor ml; digitorum);http://www.scie triceps reflex ncedirect.com/s depressed;cience/article/pii pseudomyotonia /S036350231000 of hand 5101;(difficulty in Thieme Atlas of opening b/c of Neurology 768 cervicalosteoarthritis); radicular pain (interscapular region); tricepsweakness; Brazis et al 94; http://www.jo sonline.org/ab stracts/v18n3/356.html; Waxman 51 C8 root pain in the compression due dorsal 1) n/a 1)medial to disc rami/afferent Ventrolateral arm/forearm; herniation atC7- fibers from Medulla fifth digit; T1 vertebral dorsal root (VLM)Nuclei; medial level; ipsilateral ganglion Solitary tract forearm/hand;Horner or: right nucleus paresis of Syndrome; before the (NTS), lateralmuscles (flexor cervical lesioned part reticular digitorumradiculopathy; of the root; nucleus (LRt), superficialis, nerve rootKierman 62; caudal/rostral flexor pollicis blockage; Waxman 48-ventrolateral longus, flexor trauma/birth 49 medulla; digitorum trauma;tumor 1) profundus I to of lung apex; http://www.s IV, pronator ly,phomatous ciencedirect. quadratus, infiltration; com/science/ abductorpressure lesion article/pii/S1 pollicis brevis, at elbow; 5660702020opponens traumatic palsy 00346 pollicis, flexor (from a pollicis brevis,blow/knife/glass all lumbricals, at the wrist or flexor carpi elbowfractures); ulnaris, delayed nerve abductor digiti palsy (ages afterminimi, an elbow opponens fracture/disloca- digiti minimi, tion etc +vagus flexor digiti deformity); minimi, all arthrosis; interossei,Brazis et al 94; adductor http://www.joso pollicis, nline.org/abstracextensor digiti ts/v18n3/356.ht minimi, ml; extensor carpi Thieme Atlasof ulnaris, Neurology 753, abductor 759, 776 pollicis longus, extensorpollicis longus and brevis, and extensor indicis); depressed fingerflexor reflex; razis et al 94; http://www.jo sonline.org/abstracts/v18n3/ 356.html; Thieme Atlas of Neurology 779 radicular pain(interscapular/ scapular region of nerve root); motor deficit in handmuscles T3 root decreased arachnoid dorsal Dorsal cerebellum sensationof calcifications rami/afferent Spinocerebellar (cerebellar skin (causedby fibers from Tract; cortex); (dermatome); trauma); dorsal roothttp://www. http://www. radicular myelography, ganglion ncbi.nlm.nih.ncbi.nlm.nih. pain/low back subarachnoid or: right gov/pubmed gov/pubmedpain/paralysis; hemorrhage, before the /14337566?d /14337566?d Brazis etal 94; spinal lesioned part opt=Abstract opt=Abstract http://www.ncanesthesia; of the root; &holding=np &holding=np bi.nlm.nih.govhttp://www.ncbi Kierman 62; g g /pubmed/171 .nlm.nih.gov/pu Waxman 48-49734 bmed/17149734 49 T4 root decreased intramecdullary dorsal Dorsalcerebellum sensation of tumor (spinal rami/afferent Spinocerebellar(cerebellar skin metastasis); fibers from Tract; cortex); (dermatome);arachnoid dorsal root http://www. http://www. numbness in calcificationsganglion ncbi.nlm.nih. ncbi.nlm.nih. body/both (caused by or: rightgov/pubmed gov/pubmed legs; trauma); before the /14337566?d /14337566?dbladder/bowel subarachnoid lesioned part opt=Abstract opt=Abstractdysfunction; hemorrhage; of the root; &holding=np &holding=npprogressive http://www.ncbi Kierman 62; g g weakness of .nlm.nih.gov/puWaxman 48- bilateral lower bmed/19398862; 49 extremities;http://www.ncbi radicular .nlm.nih.gov/pu pain/low back bmed/17149734pain/paralysis; Brazis et al 94; http://www.nc bi.nlm.nih.gov/pubmed/193 98862; http://www.nc bi.nlm.nih.gov /pubmed/171 49734;http://www.nc bi.nlm.nih.gov /pubmed/171 49734 T5 root decreased T5nerve root dorsal Dorsal cerebellum sensation of fistula; traumarami/afferent Spinocerebellar (cerebellar skin (particularly fibers fromTract; cortex); (dermatome); head injuries or dorsal root http://www.http://www. Brazis et al 94; penetrating ganglion ncbi.nlm.nih.ncbi.nlm.nih. http://www.nc damage to the or: right gov/pubmedgov/pubmed bi.nlm.nih.gov spine); before the /14337566?d /14337566?d/pubmed/813 http://www.ncbi lesioned part opt=Abstract opt=Abstract 3999.nlm.nih.gov/pu of the root; &holding=np &holding=np bmed/8133999Kierman 62; g g Waxman 48- 49 T6 root decreased schwannoma dorsal Dorsalcerebellum sensation of (nerve sheath rami/afferent Spinocerebellar(cerebellar skin tumor); fibers from Tract; cortex); (dermatome);http://www.scie dorsal root http://www. http://www. gait controlncedirect.com/s ganglion ncbi.nlm.nih. ncbi.nlm.nih. difficulty;cience/article/pii or: right gov/pubmed gov/pubmed tactile/S096758680600 before the /14337566?d /14337566?d hypaethesia 2384lesioned part opt=Abstract opt=Abstract below T6; of the root;&holding=np &holding=np Brazis et al 94; Kierman 62; g g http://www.scWaxman 48- iencedirect.co 49 m/science/arti cle/pii/S09675 86806002384T7 root no movement T6-T7 injury dorsal Dorsal cerebellum in lower(trauma); rami/afferent Spinocerebellar (cerebellar extremities;schwannoma fibers from Tract; cortex); gait control (tumor of nervedorsal root http://www. http://www. difficulty; sheath); ganglionncbi.nlm.nih. ncbi.nlm.nih. thermic/algic arachnoid or: right gov/pubmedgov/pubmed hypaethesia calcifications w/ before the /14337566?d/14337566?d below T7; possible lesioned part opt=Abstract opt=Abstracthttp://www.nc arachnoid of the root; &holding=np &holding=npbi.nlm.nih.gov ossification + Kierman 62; g g /pubmed/186 nerve rootWaxman 48- 62744; compression 49 http://www.sc (caused by iencedirect.cotrauma or m/science/arti interspinal cle/pii/S09675 tumor); 86806002384myelography, subarachnoid hemorrhage, spinal anethesia; http://www.ncbi.nlm.nih.gov/pu bmed/18662744; O'Rahilly et al ch 41; http://www.sciencedirect.com/s cience/article/pii /S096758680600 2384; http://www.ncbi.nlm.nih.gov/pu bmed/17149734 T8 root no movement T6-T7 injury dorsalDorsal cerebellum in lower (trauma); T7-T8 rami/afferent Spinocerebellar(cerebellar extremities; injury (trauma); fibers from Tract; cortex);complete T7 level injury dorsal root http://www. http://www.motor/sensory (trauma); ganglion ncbi.nlm.nih. ncbi.nlm.nih. deficit;lack of http://www.ncbi or: right gov/pubmed gov/pubmed sphincter/sexual.nlm.nih.gov/pu before the /14337566?d /14337566?d function andbmed/18662744; lesioned part opt=Abstract opt=Abstract control; radicu-O'Rahilly et al ch of the root; &holding=np &holding=np lar pain/low 41;Kierman 62; g g back Waxman 48- pain/paralysis; 49 http://www.ncbi.nlm.nih.gov /pubmed/186 62744; http://www.nc bi.nlm.nih.gov/pubmed/171 49734 T9 root lack of T7-T8 dorsal Dorsal cerebellumsphincter/sexual injury(trauma); rami/afferent Spinocerebellar(cerebellar function and arachnoid fibers from Tract; cortex); control;calcifications w/ dorsal root http://www. http://www. http://www.ncpossible ganglion ncbi.nlm.nih. ncbi.nlm.nih. bi.nlm.nih.gov arachnoidor: right gov/pubmed gov/pubmed /pubmed/186 ossification + before the/14337566?d /14337566?d 62745 nerve root lesioned part opt=Abstractopt=Abstract compression of the root; &holding=np &holding=np (caused byKierman 62; g g trauma); Waxman 48- myelography, 49 subarachnoidhemorrhage, spinal anesthesia; http://www.ncbi .nlm.nih.gov/pubmed/18662744; http://www.ncbi .nlm.nih.gov/pu bmed/17149734; O'Rahillyet al ch 41 T10 root bilateral T9 Injury dorsal Dorsal cerebellumabdominal (trauma); tumor rami/afferent Spinocerebellar (cerebellarmuscle pressure; fibers from Tract; cortex); paresis; tracehttp://www.ncbi dorsal root http://www. http://www. movements/.nlm.nih.gov/pu ganglion ncbi.nlm.nih. ncbi.nlm.nih. hypoethesiabmed/18662744; or: right gov/pubmed gov/pubmed (partial loss ofO'Rahilly et al ch before the /14337566?d /14337566?d sensation) in 41:lesioned part opt=Abstract opt=Abstract lower of the root; &holding=np&holding=np extremities; Kierman 62; g g lack of Waxman 48-sphincter/sexual 49 function or control; muscle spasms; Brazis et al 94;http://www.nc bi.nlm.nih.gov /pubmed/186 62745 T11 root excessivelateral disc dorsal Dorsal cerebellum protrusion of herniationrami/afferent Spinocerebellar (cerebellar abdomen causing fibers fromTract; cortex); (when compression on dorsal root http://www. http://www.inspiring); root; ganglion ncbi.nlm.nih. ncbi.nlm.nih. bilateralhttp://www.ncbi or: right gov/pubmed gov/pubmed abdominal.nlm.nih.gov/pu before the /14337566?d /14337566?d muscle bmed/18090072lesioned part opt=Abstract opt=Abstract paresis; of the root;&holding=np &holding=np Brazis et al 94 Kierman 62; g g Waxman 48- 49T12 root excessive trauma; nerve dorsal Dorsal cerebellum protrusion ofroot avulsion; rami/afferent Spinocerebellar (cerebellar abdomenassociated fibers from Tract; cortex); (when syringomyelia; dorsal roothttp://www. http://www. inspiring); tumor pressure; ganglionncbi.nlm.nih. ncbi.nlm.nih. bilateral lateral disc or: right gov/pubmedgov/pubmed abdominal herniation before the /14337566?d /14337566?dmuscle causing lesioned part opt=Abstract opt=Abstract paresis; motorcompression on of the root; &holding=np &holding=np weakness in root;Kierman 62; g g lower http://www.ncbi Waxman 48- extremity;.nlm.nih.gov/pu 49 hyperalgesia bmed/19350043; below L1; http://www.ncbiBrazis et al 94; .nlm.nih.gov/pu http://www.nc bmed/18090072bi.nlm.nih.gov /pubmed/193 50043 L1 root tibial nerve; herniation ofdorsal Dorsal cerebellum cremasteric L5/S1 disc; rami/afferentSpinocerebellar (cerebellar reflex; inguinal lateral disc fibers fromTract; cortex); region herniation dorsal root Waxman Ch Waxman Ch(groin/lower causing ganglion 5; 5; lateral regions compression on or:right http://www. http://www. of abdomen); root; before thencbi.nlm.nih. ncbi.nlm.nih. lower (L5/S1) lesioned part gov/pubmedgov/pubmed abdominal http://www.neu of the root; /14337566?d /14337566?dparesis roanatomy.wisc. Kierman 62; opt=Abstract opt=Abstract (internaledu/SClinic/Radi Waxman 48- &holding=np &holding=np oblique,culo/Radiculopat 49 g g transversus hy.htm; abdominis); http://www.ncbiWaxman 62; .nlm.nih.gov/pu Brazis et al 95 bmed/18090072 L2 rootanterior thigh meralgia dorsal Dorsal cerebellum sensory parethetica duerami/afferent Spinocerebellar (cerebellar disturbances; to compressionfibers from Tract; cortex); paresis of of nerve; lumbar dorsal rootWaxman Ch Waxman Ch body radiculopathy; ganglion 5; 5; parts: pectineuslumbar disc or: right http://www. http://www. (thigh herniation intobefore the ncbi.nlm.nih. ncbi.nlm.nih. adduction, preganglionic lesionedpart gov/pubmed gov/pubmed flexion, and region of the of the root;/14337566?d /14337566?d eversion), nerve root; Kierman 62; opt=Abstractopt=Abstract iliopsoas (thigh spinal stetosis; Waxman 48- &holding=np&holding=np flexion), trauma; 49 g g sartorius (meralgia (thigh flexionparethetica/lum and eversion), bar)http://www. quadricepsncbi.nlm.nih.gov (leg /pubmed/21294 extension), 431; and thighadductors; depression of cremasteric reflex (of L2); Brazis et al 95;http://www.nc bi.nlm.nih.gov /pubmed/204 31433; L3 root lower anteriorarachnoidal/ dorsal Dorsal cerebellum thigh, medial dural defect;rami/afferent Spinocerebellar (cerebellar knee; paresis physical traumafibers from Tract; cortex); in pectineus leading to dorsal roothttp://www. http://www. (thigh herniation of ganglion ncbi.nlm.nih.ncbi.nlm.nih. adduction, nerve root; or: right gov/pubmed gov/pubmedflexion, and nerve root before the /14337566?d /14337566?d eversion),entrapment in lesioned part opt=Abstract opt=Abstract iliopsoas (thighpseudo- of the root; &holding=np &holding=np flexion), miningocele;Kierman 62; g g sartorius lumbar Waxman 48- (thigh flexionspondylolysis; 49 and eversion), (archnoidal/dural/ quadriceps pseudo-(leg miningocele/lumbar extension), spondylolysis) and thighhttp://www.joso adductors; nline.org/pdf/v1 depressed 8i3p367.pdf;reflex of L2-L4 (patellar reflex); S1 root @dorsal lateral portion of L3level; quadri- cepts femoris weakness (knee); Brazis et al 95;http://www.jo sonline.org/pd f/v18i3p367.p df; Waxman 51 L4 root pain inlower lumbar dorsal Dorsal cerebellum back/buttock/ spondylolysis;rami/afferent Spinocerebellar (cerebellar anterlateral invading tumorsfibers from Tract; cortex); thigh/anterior involving ala of dorsal roothttp://www. http://www. leg; sensory sacrum ganglion ncbi.nlm.nih.ncbi.nlm.nih. disturbances infringing on or: right gov/pubmed gov/pubmedof nerve root; before the /14337566?d /14337566?d knee/medial tumorexcision; lesioned part opt=Abstract opt=Abstract leg; paresis inneurogenic of the root; &holding=np &holding=np muscles of hypertrophyKierman 62; g g leg/feet - (tibialis anterior Waxman 48- quadricepsmuscle) due to 49 (leg excessive extension)sarto- activity; rius (thighBrazis et al 95; flexion and http://www.joso eversion), tibi-nline.org/pdf/v1 alis anterior 8i3p367.pdf; (foot http://www.josodorsiflexion nline.org/abstrac and inversion); ts/v18n3/352.ht depressedml; patellar reflex; quadriceps femoris weakness (knee); Brazis et al95; http://www.jo sonline.org/pd f/v18i3p367.p df; http://www.josonline.org/ab stracts/v18n3/ 352.html; Waxman 51 S1 root pain in lowerpost-osteotomy dorsal VPL Primary back, buttock, surgery rami/afferentThalamus; Sensory lateral complications; fibers from Young et al Cortexthigh, calf; post-dissection dorsal root 142 (postcentral sensoryjoining of S1, S2 ganglion gyrus); disturbance of leaving nerve or:right Young et al little toe, roots at risk of before the 138-142;lateral foot, tumor invasion; lesioned part Ropper and most of the clearcell of the root; Samuels Ch 9 sole of the sarcoma (tumor Kierman 62;foot; paresis in arising from S1 Waxman 48- knee/hip/feet - nerve root);49 gluteus http://www.joso maximus (hip nline.org/abstrac extension),ts/v18n3/352.ht biceps femoris ml (knee flexion), gastrocnemius + soleus(plantar flexion of foot), flexor hallucis longus (plantar flexion offoot and terminal phalanx of great toe), flexor digitorum longus(plantar flexion of foot and all toes except the large toe), all of thesmall muscles of the foot, extensor digitorum brevis (extension of largetoe + three medial toes); S1-S2 (depressed achilles reflex);gastrocnemius weakness; lower extremity parethesia; Brazis et al 96;Waxman 51; http://www.nc bi.nlm.nih.gov /pubmed/173 41045; S2 root loweriatrogenic injury dorsal VPL Primary limb/bowel/ during surgery;rami/afferent Thalamus; Sensory bladder post-dissection fibers fromYoung et al Cortex functions; joining of S1, S2 dorsal root 142(postcentral Sensory leaving nerve ganglion gyrus); disturbances rootsat risk of or: right Young et al for calf, tumor invasion; before the138-142; posterior (surgery/tumors) lesioned part Ropper and thigh,buttock, http://www.joso of the root; Samuels Ch 9 perianalnline.org/abstrac Kierman 62; region; ts/v18n3/352.ht Waxman 48- Braziset al 96; ml; 49 http://www.jo http://www.ncbi sonline.org/ab.nlm.nih.gov/pu stracts/v18n3/ bmed/21500136 352.html S3 root Chroniclower invasion by dorsal VPL Primary back pain; tumor; sciaticarami/afferent Thalamus; Sensory impaired (nerve root fibers from Younget al Cortex Sphincter compression); dorsal root 142 (cerebrum);activity; Tarlov Cysts; ganglion Young et al Sensory Cauda Equina or:right 138-142 disturbances Syndrome(due before the for calf, to spinalcord lesioned part posterior compression by of the root; thigh, buttock,drug-induced Kierman 62; perianal loculation); Waxman 48- region;(Invasion by 49 Brazis et al 96; tumor)http://w http://www.ncww.josonline.org bi.nlm.nih.gov /abstracts/v18n3 /pubmed/212 /352.html;86446; http://www.ncbi http://www.nc .nlm.nih.gov/pu bi.nlm.nih.govbmed/21500136; /pubmed/180 http://www.ncb 34793; i.nlm.nih.gov/pubmed/21286446

TABLE 5 Body Part(s) Region of That Have CNS That is Diminished Cause ofImpaired Function Impairment Input Region Output Region Connection smallcenter i)loss of a) Syringomyelia posterior root ventral cerebrallesions pain/temp b) Chiari Type ganglion posterior cortex(spinothalamic sensibilities in I, II, Dandy axons aka nucleus of(primary tract the segment Walker dorsal root thalamus sensorydecussating w/lesion Malformations, or: right or: right after cortex orSI fibers) (Decussating traumatic before lesioned part area); fibers inthe paraplegia, lesioned part of tract; Young et al ventral white spinaltrauma, of tract; Kierman 292; 149-150; commisure) - spinal cord Snell142; Waxman anethesia for tumors, Waxman Ch 5 56, 57, 58 shoulders/upperarachnoiditis, Sec III; limbs; muscle myelitis; wasting in a) Waxman 66,upper limbs; 68; ii)anterior horn Kierman 77 atrophy/paresis/ b)Braziset al areflexia; 105 i)Waxman 68; ii) Brazis et al 105 posterior/lateralcervical cord; a) Posterolateral dorsal root dorsal primary columns inthoratic cord; Column Disease or: right column sensory upper spinallumbar cord (lack of B12); before nuclei cortex (SI cord (dorsaldegeneration; AIDS; HTLV-1; lesioned part (cuneate area); column-medialparethesia in tropical spastix of tract; nuclei) Kierman 292; lemniscusfeet/hands; paraperesis; Adams' and or: right after Young et al pathway)aka Dorsal column cervical Victor's lesioned part 149-150; dorsal cornuor dysfunction spondylosis Neurology Ch of tract; http://www. lateral(spine/skin (chronic disk 9 http://www. ncbi.nlm.nih. cornu/hornsensation); degeneration); google.com/ gov/pubmed Brazis et al b)sensoryurl?sa=t&sou /3096488; 106; ataxia/loss of rce=web&cd http://www.Tsementzis 208 proprioception =1&ved=0CB ncbi.nlm.nih. and vibrationoQFjAA&url= gov/pubmed sense/bilateral http%3A%2F /8899636;spasticity/hyper %2Fwww.bio http://www. reflexia med.cas.cz% google.com/c) trauma; 2Fphysiolres url?sa=t&sou a)Bravis 106; %2Fpdf%2F5 rce=web&cdhttp://www.acc 3%2520Suppl =1&ved=0CB essmedicine.co %25201%2F5oQFjAA&url= m/content.aspx 3_S125.pdf& http%3A%2F ?aID=2319519&ei=etY2TuP9L %2Fwww.bio searchStr=cervic IrZgQf_sdnsD med.cas.cz%al+spine+diseas A&usg=AFQj 2Fphysiolres e; b) Differential CNG_O2zJSpJ%2Fpdf%2F5 diagnosis in KjPhNyxivc- 3%2520Suppl neurology and VBjOpWww%25201%2F5 neurosurgery: a 3_S125.pdf& clinician's ei=etY2TuP9L pocketguide IrZgQf_sdnsD By S. A. A&usg=AFQj Tsementzis 208 CNG_O2zJSpJ c)KjPhNyxivc- http://www.ncbi VBjOpWww .nlm.nih.gov/pu bmed/3096488complete a) Vertebral 1) traumatic undamaged undamaged neocortextransection of Tenderness spine injuries parts of all parts of all(cingulate spinal cord (percussion?) (stabbing/gunfire/ ascendingascending gyrus) for (transverse b) inhibition of diving into a tractsfrom tracts from sensory myelopathy) reflex shallow pool), below theabove the ascending anywhere in tumor (e.g., lesion; all lesion; alltracts; the cord below metastatic descending descending Kierman 289 thelesion; carcinoma, tracts from tracts from Spincter lymphoma), above thebelow the disturbance; multiple lesion; lesion; back/radicularsclerosis,, Brazis et al Brazis et al pain c)Tactile vascular 103 103stimulus above disorders, spinal lesion epidural d) all hematomamotor/sensory (usually functions secondary to below the levelanticoagulants) of lesion; or abscess, a) Current paraneoplasticDiagnosis and myelopathy, Treatment autoimmune (Keith Stone) disorders,ch 35 herniated b)Total intervertebral Transverse disc, and Lesions ofthe parainfectious Spinal Cord or postvaccinal c)Adam's and syndromesVictor's 2) herpes Neurology, simplex, ch44: influenza, http://www.acEpstein-Barr cessmedicine.c virus), om/content.as immunisationspx?aID=36406 (smallpox, 29&searchStr= influenza) and transverse+myintoxication elitis (baclofen, d) Brazis et al penicillins, lead);; 103Systemic Lupus; 3)tetraplegia (if upper cervical cord transection);paraplegia iif transection between the cervical and lumbosacralenlargements; 1. Brazis et al 103; Jeffrey et al Arch Neurol. 1993 May;50(5): 532-5.; 2)http://ard.bmj .com/content/5 9/2/120.abstrac t 3)Kierman 76 Dorsal Root elecated ALS, HIV/AIDs, peripheral dorsal medullaganglion (aka touch-pressure tumor nervous (posterior) oblongata;posterior root sensation (particularly system's horn cells cerebellum;ganglion) thresholds Small Cell Lung afferent/sen- or: part of ColorAtlas of (dorsal Cancer SCLC); sory fibers the dorsal Textboom ofcolumn/spino- Vitamin B6 or: part of root right Human cerebellar tractintoxication (ex: dorsal root after the Anatomy: dysfunction bodybuilding right before lesioned Nervous due to regimen, PMS the lesionedganglion; system and demyelination); treatment); ganglion; Color Atlasof Sensory increased chemotherapy Brazis et al 89 Textboom of Organs50-56 sense of drugs especially Human pain(hyperal- platinum basedAnatomy: gesia)/pain due agents (ex: Nervous to negligible Ciplatin,system and stimulus(allo- carboplatin, Sensory dynia); gait oxaliplatinetc); Organs 50-56 impairment, Guillian Barre, autonomic Miller Fishersystem Sundrome, impairment; opthalmoplegia; (vitamin rheumatoidoverdose) loss arthritis, of tendon Sjogren's reflex, syndrome,progressive Epstein-barr, sensory ataxia; measles, bilnk reflexvaricella zoster; abnormalities; (ALS) (ALS) http://www.ncbihttp://www.nc .nlm.nih.gov/pu bi.nlm.nih.gov/ bmed/17929040; pubmed/1792http://www.ncbi 9040; .nlm.nih.gov/pu http://www.nc bmed/20628092;bi.nlm.nih.gov/ http://pn.bmj.co pubmed/2062 m/content/10/6 8092;/326.full http://jn.physi ology.org/cont ent/84/2/798.f ull;http://pn.bmj. com/content/1 0/6/326.full Anterior horn upper motorSpinal muscular ventral root dorsal Color Atlas of (aka anterior neurons(any Atrophies; ALS (sensory horn/columns; Textboom of column/ventralstriated (degeneration of nerves); Bonica's Human horn) muscle); uppermotor Bonica's Management Anatomy: progressive neurons/Charcot'sManagement of Pain 1497; Nervous weakness of Lou Gehrig's); of Pain1497; http://onlinel system and the bulbar, progressive http://onlineliibrary.wiley.c Sensory limb/thoracic/ bulbar palsy, brary.wiley.coom/doi/10.1 Organs 50 abdominal progressive m/doi/10.100 002/cne.901musculature; muscular 2/cne.901790 790304/pdf upper motor atrophy (lower304/pdf neuron motor spasticity/ syndrome), paresis; primary lateralBrazis et al sclerosis (upper 107-109; motor http://jnnp.bm syndrome),astro- j.com/content/ cytosis; trauma; 74/9/1250.abs stroke tract;(ipsilateral Tsementzis 209 cerebral peduncular atrophy); non- traumaticcardiac arrest (due to spinal cord ischemia); Brazis et al 109,http://jnnp.bmj. com/content/74 /9/1250.abstrac t; http://www.ncbi.nlm.nih.gov/pu bmed/18024577; http://www.ncbi .nlm.nih.gov/pubmed/7884198 Upper Cervical contralateral Cruciate medial cerebral Cordupper Paralysis lemniscus; hemisphere (cervicomedullary extremity(caused by Smith et al (sensory- junction paresis and traumatic 34-35motor injuries or ipsilateral injuries mostly); cortex); malformations)lower http://www.upt cerebellum; extremity odate.com/cont Smith et alparesis; lower ents/anatomy- 34-35; extremity and-localization-http://www. weakness of-spinal-cord- ncbi.nlm.nih. (musclesdisorders/abstra gov/pubmed proximal to the ct/18 /19793979 lesion);facial/limb hypethesia; Brazis et al 112; http://www.up todate.com/contents/anatom y-and- localization-of- spinal-cord- disorders/abstract/18 Complete ipsilateral zone Brown-Sequard below the dorsal cerebralhemisection of of cutaneous Syndrome lesion in column cortex spinal cordanethesia in (stab/gunshot dorsal nuclei (primary (dorsal column) thesegment wounds); column; (cuneate sensory of the lesion syringomeliabelow the nuclei); cortex or SI (due to (loss of lesion in http://www.area); undecussated pain/temperature spinothalamic google.com/ Kierman292; afferent fibers sensation at tract; below url?sa=t&sou Young et althat had multiple levels); the lesion for rce=web&cd 149-150; alreadyspinal cord any afferent =1&ved=0CB http://www. entered the tumor;fibers; oQFjAA&url= ncbi.nlm.nih. spinal cord); hematomyelia Waxman 68http%3A%2F gov/pubmed loss of (hemorrhage %2Fwww.bio /3096488;propioceptive/ into the spinal med.cas.cz% http://www. vibratory/2-ptcord); 2Fphysiolres ncbi.nlm.nih. discrimination Waxman 68; %2Fpdf%2F5gov/pubmed sense below Brazis et al 105 3%2520Suppl /8899636; the lesion%25201%2F5 http://www. (dorsal column 3_S125.pdf& google.com/ damage);ei=etY2TuP9L url?sa=t&sou spastic IrZgQf_sdnsD rce=web&cd weakness atA&usg=AFQj =1&ved=0CB level of lesion; CNG_O2zJSpJ oQFjAA&url= loss ofKjPhNyxivc- http%3A%2F temperature/ VBjOpWww %2Fwww.bio pain sensationmed.cas.cz% below the level 2Fphysiolres (decussated %2Fpdf%2F5spinothalamic 3%2520Suppl tract fibers %25201%2F5 damage); 3_S125.pdf&Waxman 68; ei=etY2TuP9L Brazis et al 105 IrZgQf_sdnsD A&usg=AFQjCNG_O2zJSpJ KjPhNyxivc- VBjOpWww myelin sheaths axon Multiple node ofnext node of of axons (PNS + degeneration; Sclerosis; Acute ranvierbefore ranvier after CNS) failure of signal inflammatory the lesion; thelesion in transmission; demyelinating Waxman 25 the direction slowing ofpolyneuropathy of the action nerve (AIDP), Guillain potentialconduction; Barre; traumatic pathway; motor brain injury (for Waxman 25weakness, oligodendrite paraparesis, injuries) + paresthesia subsequent(numbing of degeneration of skin), diplopia white matter (doublevision), tracts; Miller- nystagmus Fischer (involuntary Syndrome; eyecopper movement), deficiency; tremor, ataxia, Waxman 302; impairment ofDeLisa et al 899; deep Adams and sensation, and Victor's bladderNeurology Ch 36; dysfunction; http://www.ncbi blindness, .nlm.nih.gov/putremor; bmed/21669255; Young et al 13; http://www.ncbi Waxman.nlm.nih.gov/pu 24, 38, 302; bmed/21631649; Adams and http://www.ncbiVictor's .nlm.nih.gov/pu Neurology Ch bmed/20685220 36

TABLE 6 Region of CNS That is Impaired Input Region Output RegionConnection I Olfactory bipolar cells in Olfactory Bulb Olfactory Nerveolfactory (glomeruli) association cortex epithelium or: part of normal(frontal lobe); (cilia at surface of nerve right after Kierman 262-263epithelium in the lesion; superior nasal Young et al 262; concha + upper⅓ http://www.ncbi.nl of nasal septum) m.nih.gov/pubmed or: part ofnormal /21704681 nerve before lesion; Young et al 270; http://www.blackwellpublishing.com /patestas/chapters /15.pdf VIII Vestibular vestibularganglion Vestibular nuclei Vestibulocerebellum (Vestibulocochlear akascarpa's or: part of normal aka Nerve) ganglion nerve right afterflocculonodar lobe (hair cells of the lesion; of cerebellum; ampullarycrests in Young et al 262; Kierman 335 semicircular Kierman 335;ducts/maculae of Shumway-Cook 69 saccule and utricle) or: part of normalnerve before lesion; Young et al 272; Shumway-Cook 69 VIII Cochlear oticganglion Cochlear nuclei primary auditory (Vestibulocochlear(auriculotemporal (second-order area of cerebral Nerve) nerve supplyingneurons) cortex (aka paratoid gland) or: part of normal superiortemporal or: part of normal nerve right after gyrus); nerve before thelesion; Kierman 326 lesion; Young et al 262, Schuenke et al 150; 161Young et al 272; V Trigeminal trigeminal ganglion spinal trigeminal VPMThalamus Nerve aka nucleus (caudal); (then to primarysublingual/Langley's principal trigeminal sensory cortex); ganglion(free nucleus Waxman ch 8 nerve ends in or: part of normal muscous mouthnerve right after membrane aka oral the lesion; mucosa; anterior Younget al 270; scalp/face; free nerve endings in tympanic membrane,supratentorial meninges); submandibular ganglion or: part of normalnerve before lesion; Young et al 270; http://www.ncbi.nlm.nih.gov/pubmed /13886632; http://www.scienc edirect.com/science/article/pii/S0304 394010003423 VII Facial Nerve Pterygopaline SolitaryNucleus ipsilateral cerebral ganglion; or: part of normal cortex(primary submandibular nerve right after gustatory cortex); ganglion;the lesion; Kierman 131; geniculate ganglion Waxman 113-115 Young et al193- (taste buds in 194 anterior ⅔ of mouth) or: part of normal nerve(chorda tympani fibers) before lesion; Young et al 237, 271; Waxman 113IX otic ganglion Solitary Nucleus cerebral cortex Glossopharyngeal(auriculotemporal (taste + (post central Nerve nerve supplyingchemoreceptor gyrus); paratoid gland) and baroreceptor Kierman 214, 215or: part of normal reflexes)/Spinal nerve before Trigeminal Nucleuslesion; (general Young et al. 237; sensations) Waxman 257; or: part ofnormal Snell 403, 405 nerve right after the lesion; Young et al 269;Brazis et al 325 X Vagus Nerve cardiac ganglion; Solitary nucleuscerebral cortex; bronchial ganglion; (inferior Young et al 253 pulmonaryganglion)/Spinal ganglion; enteric trigeminal ganglion; intestinalnucleus(superior) ganglion; proximal or: part of normal colon ganglionnerve right after or: part of normal the lesion; nerve before Young etal 273; lesion; Young et al 237; http://www.ncbi.nl m.nih.gov/pubmed/2435865; http://www.ncbi.nl m.nih.gov/pubmed /8946336

Although in the examples above we describe and build encoders in amodular fashion with a specific set of algorithmic steps, it is evidentthat algorithms or devices with substantially similar input/outputrelationships can be built with different steps, or in a non-modularfashion, for example, by combining any two or three of the steps in to asingle computational unit, such as an artificial neural network.

Given the encoders of the present disclosure, it is possible to generatedata sets, without the collection of physiological data, that can beused, for example, to develop parameters for alternate spatiotemporaltransformations, or to train a neural net, to produce identical orsimilar output using methods that are well known in the art. Theexplicit description of the encoders thus enables the development ofprosthetics, as well as other devices, such as, but not limited to,bionics (e.g., devices providing supranormal capability) and robotics(e.g., artificial sensing systems).

The scope of the present invention is not limited by what has beenspecifically shown and described herein. Those skilled in the art willrecognize that there are suitable alternatives to the depicted examplesof materials, configurations, constructions and dimensions. Numerousreferences, including patents and various publications, are cited anddiscussed in the description of this invention. The citation anddiscussion of such references is provided merely to clarify thedescription of the present invention and is not an admission that anyreference is prior art to the invention described herein. All referencescited and discussed in this specification are incorporated herein byreference in their entirety.

While various inventive embodiments have been described and illustratedherein, those of ordinary skill in the art will readily envision avariety of other means and/or structures for performing the functionand/or obtaining the results and/or one or more of the advantagesdescribed herein, and each of such variations and/or modifications isdeemed to be within the scope of the inventive embodiments describedherein. More generally, those skilled in the art will readily appreciatethat all parameters, dimensions, materials, and configurations describedherein are meant to be exemplary and that the actual parameters,dimensions, materials, and/or configurations will depend upon thespecific application or applications for which the inventive teachingsis/are used. Those skilled in the art will recognize, or be able toascertain using no more than routine experimentation, many equivalentsto the specific inventive embodiments described herein. It is,therefore, to be understood that the foregoing embodiments are presentedby way of example only and that, within the scope of the appended claimsand equivalents thereto, inventive embodiments may be practicedotherwise than as specifically described and claimed. Inventiveembodiments of the present disclosure are directed to each individualfeature, system, article, material, kit, and/or method described herein.In addition, any combination of two or more such features, systems,articles, materials, kits, and/or methods, if such features, systems,articles, materials, kits, and/or methods are not mutually inconsistent,is included within the inventive scope of the present disclosure.

The above-described embodiments can be implemented in any of numerousways. For example, the embodiments may be implemented using hardware,software or a combination thereof. When implemented in software, thesoftware code can be executed on any suitable processor or collection ofprocessors, whether provided in a single computer or distributed amongmultiple computers.

Further, it should be appreciated that a computer may be embodied in anyof a number of forms, such as a rack-mounted computer, a desktopcomputer, a laptop computer, or a tablet computer. Additionally, acomputer may be embedded in a device not generally regarded as acomputer but with suitable processing capabilities, including a PersonalDigital Assistant (PDA), a smart phone or any other suitable portable orfixed electronic device.

Also, a computer may have one or more input and output devices. Thesedevices can be used, among other things, to present a user interface.Examples of output devices that can be used to provide a user interfaceinclude printers or display screens for visual presentation of outputand speakers or other sound generating devices for audible presentationof output. Examples of input devices that can be used for a userinterface include keyboards, and pointing devices, such as mice, touchpads, and digitizing tablets. As another example, a computer may receiveinput information through speech recognition or in other audible format.

Such computers may be interconnected by one or more networks in anysuitable form, including a local area network or a wide area network,such as an enterprise network, and intelligent network (IN) or theInternet. Such networks may be based on any suitable technology and mayoperate according to any suitable protocol and may include wirelessnetworks, wired networks or fiber optic networks.

A computer employed to implement at least a portion of the functionalitydescribed herein may comprise a memory, one or more processing units(also referred to herein simply as “processors”), one or morecommunication interfaces, one or more display units, and one or moreuser input devices. The memory may comprise any computer-readable media,and may store computer instructions (also referred to herein as“processor-executable instructions”) for implementing the variousfunctionalities described herein. The processing unit(s) may be used toexecute the instructions. The communication interface(s) may be coupledto a wired or wireless network, bus, or other communication means andmay therefore allow the computer to transmit communications to and/orreceive communications from other devices. The display unit(s) may beprovided, for example, to allow a user to view various information inconnection with execution of the instructions. The user input device(s)may be provided, for example, to allow the user to make manualadjustments, make selections, enter data or various other information,and/or interact in any of a variety of manners with the processor duringexecution of the instructions.

The various methods or processes outlined herein may be coded assoftware that is executable on one or more processors that employ anyone of a variety of operating systems or platforms. Additionally, suchsoftware may be written using any of a number of suitable programminglanguages and/or programming or scripting tools, and also may becompiled as executable machine language code or intermediate code thatis executed on a framework or virtual machine.

In this respect, various inventive concepts may be embodied as acomputer readable storage medium (or multiple computer readable storagemedia) (e.g., a computer memory, one or more floppy discs, compactdiscs, optical discs, magnetic tapes, flash memories, circuitconfigurations in Field Programmable Gate Arrays or other semiconductordevices, or other non-transitory medium or tangible computer storagemedium) encoded with one or more programs that, when executed on one ormore computers or other processors, perform methods that implement thevarious embodiments of the invention discussed above. The computerreadable medium or media can be transportable, such that the program orprograms stored thereon can be loaded onto one or more differentcomputers or other processors to implement various aspects of thepresent invention as discussed above.

The terms “program” or “software” are used herein in a generic sense torefer to any type of computer code or set of computer-executableinstructions that can be employed to program a computer or otherprocessor to implement various aspects of embodiments as discussedabove. Additionally, it should be appreciated that according to oneaspect, one or more computer programs that when executed perform methodsof the present invention need not reside on a single computer orprocessor, but may be distributed in a modular fashion amongst a numberof different computers or processors to implement various aspects of thepresent invention.

Computer-executable instructions may be in many forms, such as programmodules, executed by one or more computers or other devices. Generally,program modules include routines, programs, objects, components, datastructures, etc. that perform particular tasks or implement particularabstract data types. Typically the functionality of the program modulesmay be combined or distributed as desired in various embodiments.

Also, data structures may be stored in computer-readable media in anysuitable form (e.g., non-transitory media). For simplicity ofillustration, data structures may be shown to have fields that arerelated through location in the data structure. Such relationships maylikewise be achieved by assigning storage for the fields with locationsin a computer-readable medium that convey relationship between thefields. However, any suitable mechanism may be used to establish arelationship between information in fields of a data structure,including through the use of pointers, tags or other mechanisms thatestablish relationship between data elements.

Also, various inventive concepts may be embodied as one or more methods,of which an example has been provided. The acts performed as part of themethod may be ordered in any suitable way. Accordingly, embodiments maybe constructed in which acts are performed in an order different thanillustrated, which may include performing some acts simultaneously, eventhough shown as sequential acts in illustrative embodiments.

As used herein the term “light” and related terms (e.g. “optical”) areto be understood to include electromagnetic radiation both within andoutside of the visible spectrum, including, for example, ultraviolet andinfrared radiation.

As used herein the term “sound” and related terms (e.g. “audio”) are tobe understood to include vibratory waves in any medium (e.g., gas,fluid, liquid, solid, etc.) both within and outside of the spectrumaudible to humans, including, for example, ultrasonic frequencies.

All definitions, as defined and used herein, should be understood tocontrol over dictionary definitions, definitions in documentsincorporated by reference, and/or ordinary meanings of the definedterms.

Variations, modifications and other implementations of what is describedherein will occur to those of ordinary skill in the art withoutdeparting from the spirit and scope of the invention. While certainembodiments of the present invention have been shown and described, itwill be obvious to those skilled in the art that changes andmodifications may be made without departing from the spirit and scope ofthe invention. The matter set forth in the foregoing description andaccompanying drawings is offered by way of illustration only and not asa limitation.

What is claimed is:
 1. A method improving or restoring neural functionin a mammalian subject in need thereof, the method comprising: using aninput receiver to record an input signal generated by a first set ofnerve cells; using an a encoder unit comprising a set of encoders togenerate a set of coded outputs in response to the input signal, whereingenerating the set of coded outputs comprises transforming the inputsignal based on experimental neural function data of an unimpairedsubject, wherein the experimental neural function data comprises aresponse in the unimpaired subject corresponding to the first set ofnerve cells, and wherein the transforming the input signal is furtherbased on a difference between the response in the unimpaired subject andthe input signal generated by the first set of nerve cells; using theencoded outputs to drive an output generator; and using an outputgenerator to activate a second set of nerve cells wherein the second setof nerve cells is separated from the first set of nerve cells byimpaired set of signaling cells; wherein the second set of nerve cellsproduces a response that is substantially the same as the response in anunimpaired subject.
 2. The method of claim 1, wherein: the first set ofnerve cells comprises supplementary motor area neurons; the second setof nerve cells comprises spinal motor neurons; and the impaired set ofsignaling cells comprises primary motor cortex neurons.
 3. The method ofclaim 1, comprising: generating the input signal as a time resolvedseries of values {right arrow over (a)} corresponding to the pattern ofneural activity generated in the first set of nerve cells; andtransforming the values {right arrow over (a)} to a time resolved seriesof output values {right arrow over (c)} by applying a transformation. 4.The method of claim 3, wherein {right arrow over (c)} is a vector valuedfunction, wherein each element of the vector is a value corresponding toa firing rate of a single cell or small group of cells from the secondset of nerve cells.
 5. The method of claim 4, wherein {right arrow over(c)} is a vector valued function, wherein each element of the vector isa value corresponding to the total firing rate of second set of nervecells.
 6. The method of claim 4, wherein {right arrow over (c)} is avector valued function, wherein each element of the vector is a valuecorresponding to the total firing rate of a respective subpopulation ofthe second set of nerve cells.
 7. The method of claim 6, wherein thesecond set of nerve cells comprises motor neurons, and eachsubpopulation innervates a different respective muscle.
 8. The method ofclaim 3, wherein the transformation comprises: a set of spatiotemporallinear filters; and a nonlinear function.
 9. The method of claim 8,wherein the transformation is characterized by a set of parameters; andwherein the set of parameters corresponds to a result of fitting thetransformation to experimental data obtained by: exposing an unimpairedsubject to a broad range of reference stimuli; recording a firstresponse in the unimpaired subject corresponding to the first set ofnerve cells; recording a second response in the unimpaired subjectcorresponding to the second set of nerve cells.
 10. The method of claim9, wherein the second response comprises the firing rate of individualnerve cells.
 11. The method of claim 9, wherein the spatiotemporalfilters are parameterized by a set of K weights.
 12. The method of claim11, wherein K is in the range of 5-20.
 13. The method of claim 9,wherein the nonlinear function is parameterized as a cubic splinefunction with M knots.
 14. The method of claim 13, wherein M is in therange of 2-20.
 15. The method of claim 9, wherein the spatiotemporallinear filters operate over P time bins, each having a duration Q. 16.The method of claim 15, wherein P is in the range of 5-20.
 17. Themethod of claim 16, wherein Q is in the range of 10 ms-100 ms.
 18. Themethod of claim 9, wherein the broad range of reference stimulicomprises at least one chosen from the list consisting of: motion in anenvironment comprising one or more obstacles; manipulation of objectshaving different weights; and moving a cursor to one of severallocations on a display.
 19. A device improving or restoring neuralfunction in a mammalian subject in need thereof, the device comprising:an input receiver configured to record an input signal generated by afirst set of nerve cells; an output generator configured to activate asecond set of nerve cells, wherein the second set of nerve cells isseparated from the first set of nerve cells by an impaired set ofsignaling cells; and an encoder unit comprising a set of encoders thatgenerate a set of coded outputs in response to the input signal, whereinthe encoder unit is further configured to transform the input signalbased on experimental neural function data of an unimpaired subject,wherein the experimental neural function data comprises a response inthe unimpaired subject corresponding to the first set of nerve cells,and wherein the transforming the input signal is further based on adifference between the response in the unimpaired subject and the inputsignal generated by the first set of nerve cells; and wherein the set ofcoded outputs control the output generator to activate the second set ofnerve cells to produce a response to the input signal that issubstantially the same as the response in an unimpaired subject.
 20. Anon-transitory computer readable media having computer-executableinstruction comprising instruction for executing steps comprising:recording an input signal generated by a first set of nerve cells; usingan a encoder unit comprising a set of set of encoders to generate a setof coded outputs in response to the input signal, wherein generating theset of coded outputs comprises transforming the input signal based onexperimental neural function data of an unimpaired subject, wherein theexperimental neural function data comprises a response in the unimpairedsubject corresponding to the first set of nerve cells, and wherein thetransforming the input signal is further based on a difference betweenthe response in the unimpaired subject and the input signal generated bythe first set of nerve cells, and using the coded outputs to control anoutput generator to activate a second set of nerve cells wherein thesecond set of nerve cells is separated from the first set of neurons byan impaired set of signaling cells; wherein the second set of nervecells produces a response to the input signal that is substantially thesame as the response in an unimpaired subject.